Patent Publication Number: US-2023162471-A1

Title: Information processing apparatus, information processing method and recording medium

Description:
TECHNICAL FIELD 
     The present disclosure relates to a technical field of an information processing apparatus, an information processing method and a recording medium that are configured to extract a key point (namely, a feature point) of a target object from an image in which the target object is included, for example. 
     BACKGROUND ART 
     A Patent Literature 1 discloses one example of an information processing apparatus that is configured to extract a key point (namely, a feature point) of a target object from an image in which the target object is included. Specifically, the Patent Literature 1 discloses a feature point extraction apparatus that extracts, from an image in which a person is included, a feature point of a face of the person that is used for a face authentication of the person. 
     Additionally, there are Patent Literatures 2 to 6 as a background art document relating to the present disclosure. 
     CITATION LIST 
     Patent Literature 
     Patent Literature 1: WO2020/095400A1 
     Patent Literature 2: JP2018-045437A 
     Patent Literature 3: JP2017-142772A 
     Patent Literature 4: JP2011-090702A 
     Patent Literature 5: JP2008-006149A 
     Patent Literature 6: WO2018/051836A1 
     SUMMARY 
     Technical Problem 
     It is an example object of the present disclosure to provide an information processing system, an information processing method and a recording medium that aims to an improvement of a technique disclosed in the background art document. 
     Solution to Problem 
     One example aspect of an information processing apparatus includes: a reducing unit that generates a second image by reducing a first image in which a target object is included; a first extracting unit that extracts, as a first key point, a key point of the target object from the second image; a setting unit that sets a target area that designates a part of the first image based on the first key point; and a second extracting unit that extracts, as a second key point, a key point of the target object from a target image of the first image that is included in the target area. 
     One example aspect of an information processing method includes: generating a second image by reducing a first image in which a target object is included; extracting, as a first key point, a key point of the target object from the second image; setting a target area that designates a part of the first image based on the first key point; and extracting, as a second key point, a key point of the target object from a target image of the first image that is included in the target area. 
     One example aspect of a recording medium is a recording medium on which a computer program that allows a computer to execute an information processing method is recorded, the information processing method includes: generating a second image by reducing a first image in which a target object is included; extracting, as a first key point, a key point of the target object from the second image; setting a target area that designates a part of the first image based on the first key point; and extracting, as a second key point, a key point of the target object from a target image of the first image that is included in the target area. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a block diagram that illustrates an entire configuration of a key point extraction system in a first example embodiment. 
         FIG.  2    is a block diagram that illustrates a configuration of a key point extraction apparatus in the first example embodiment. 
         FIG.  3    is a flow chart that illustrates a flow of a key point extraction operation that is performed by the key point extraction apparatus in the first example embodiment. 
         FIG.  4    is a planar view that illustrates one example of a key point of an iris that is extracted from a reduced image. 
         FIG.  5    is a planar view that illustrates one example of a target area. 
         FIG.  6    is a planar view that illustrates one example of the target area. 
         FIG.  7    is a planar view that illustrates one example of the key point of the iris that is extracted from a target image. 
         FIG.  8    is a block diagram that illustrates a configuration of a key point extraction apparatus in a second example embodiment. 
         FIG.  9    is a flow chart that illustrates a flow of a key point extraction operation that is performed by the key point extraction apparatus in the second example embodiment. 
         FIG.  10    conceptually illustrates a translation processing that translates a person image. 
         FIG.  11    conceptually illustrates a rotation processing that rotates the person image. 
         FIG.  12    conceptually illustrates a scaling processing that scales the person image. 
         FIG.  13    is a block diagram that illustrates a configuration of a key point extraction apparatus in a third example embodiment. 
         FIG.  14    is a flow chart that illustrates a flow of a key point extraction operation that is performed by the key point extraction apparatus in the third example embodiment. 
         FIG.  15    is a block diagram that illustrates a configuration of a key point extraction apparatus (an iris authentication apparatus) in a fourth example embodiment. 
         FIG.  16    is a flow chart that illustrates a flow of a key point extraction operation (an iris authentication operation) that is performed by the key point extraction apparatus in the third example embodiment. 
         FIG.  17    is a block diagram that illustrates a configuration of a key point extraction apparatus (an iris authentication apparatus) in a fifth example embodiment. 
     
    
    
     DESCRIPTION OF EXAMPLE EMBODIMENTS 
     Next, an example embodiment of an information processing apparatus, an information processing method and a recording medium will be described with reference to the drawings. In the below described description, the example embodiment of the information processing apparatus, the information processing method and the recording medium will be described by using a key point extraction system SYS. 
     The key point extraction system SYS is configured to extract a key point KP of a target object from an image in which the target object is included. The below described description explains an example in which the key point extraction system SYS is configured to extract the key point KP of a person that is included in a person image IMG 1  from the person image IMG 1  in which the person (namely, a living body) that is one example of the target object is included. However, the key point extraction system SYS may be configured to extract the key point KP of any target object that is included in an image from the image in which any target object that is different from the person is included. A living body other than a human (for example, at least one of a mammal such as a dog, a cat and so on, a bird such as a sparrow and so on, a reptile such as a snake and so on, an amphibia such as a frog and so on and a fish such as a goldfish and so on) is one example of the target object. An object that is not the living body is another example of the target object. A robot that imitates the human or an animal is one example of the object that is not the living body. 
     Moreover, the below described description explains an example in which the key point extraction system SYS is configured to extract the key point KR of an iris of the person that is included in the person image IMG 1  from the person image IMG 1 . This key point extraction system SYS may be used as an iris authentication system described in detail later. The iris authentication system is a system that is configured to authenticate the person by using the iris. However, the key point extraction system SYS may be configured to extract the key point KR of any part of the person that is included in the person image IMG 1  from the person image IMG 1 . A part that is usable for authenticating the person is one example of any part of the person. A face that is usable for a face authentication is another one example of the part that is usable for authenticating the person. A finger on which a fingerprint is formed that is usable for a fingerprint authentication is another one example of the part that is usable for authenticating the person. A hand on which a palm print is formed that is usable for a palm print authentication is another one example of the part that is usable for authenticating the person. A finger in which a pattern of a vein is formed that is usable for a vein authentication is another one example of the part that is usable for authenticating the person. 
     Next, the key point extraction system SYS will be described in more detail with reference to the drawings. 
     (1) Key Point Extraction System SYS in First Example Embodiment 
     Firstly, the key point extraction system SYS in a first example embodiment will be described. Note that the key point extraction system SYS in the first example embodiment is referred to as a “key point extraction system SYSa” in the below described description. 
     (1-1) Entire Configuration of Key Point Extraction System SYSa 
     Firstly, with reference to  FIG.  1   , an entire configuration of the key point extraction system SYSa in the first example embodiment will be described.  FIG.  1    is a block diagram that illustrates the entire configuration of the key point extraction system SYSa in the first example embodiment. 
     As illustrated in  FIG.  1   , the key point extraction system SYSa includes a camera  1  and a key point extraction apparatus  2  that is one specific example of an “information processing apparatus”. The key point extraction system SYSa may include a single camera  1  or may include a plurality of cameras  2 . The camera  1  and the key point extraction apparatus  2  are configured to communicate with each other through a communication network  3 . The communication network  3  may include a wired communication network. The communication network  3  may include a wireless communication network. 
     The camera  1  is an imaging apparatus that is configured to capture an image of an imaging target range. The camera  1  includes a processing for generating an image in which the imaging target range is included by capturing the imaging target range. Since the key point extraction system SYSa extracts the key point KP of the iris of the person as described above, the person usually exists in the imaging target range. In this case, the camera  1  generates the person image IMG 1  in which the person is included by capturing the image of the person. Especially, the camera  1  generates the person image IMG 1  in which a face (especially, at least a part of the face including the iris and a part around the iris) of the person is included by capturing the image of the face (especially, at least a part of the face including the iris and a part around the iris) of the person. The camera  1  outputs the generated person image IMG 1  to the key point extraction apparatus  2 . Specifically, the camera  1  transmits the generated person image IMG 1  to the key point extraction apparatus  2  through the communication network  3 . 
     The key point extraction apparatus  2  receives the person image IMG 1  transmitted from the camera  1  through the communication network  3 . The key point extraction apparatus  2  performs a key point extraction operation for extracting the key point KP of the iris of the person that is included in the person image IMG 1  from the received person image IMG 1 . 
     (1-2) Configuration of Key Point Extraction Apparatus  2   
     Next, with reference to  FIG.  2   , a configuration of the key point extraction apparatus  2  in the first example embodiment will be described.  FIG.  2    is a block diagram that illustrates the configuration of the key point extraction apparatus  2  in the first example embodiment. 
     As illustrated in  FIG.  2   , the key point extraction apparatus  2  includes an arithmetic apparatus  21 , a storage apparatus  22  and a communication apparatus  23 . Furthermore, the key point extraction apparatus  2  may include an input apparatus  24  and an output apparatus  25 . However, the key point extraction apparatus  2  may not include at least one of the input apparatus  24  and the output apparatus  25 . The arithmetic apparatus  21 , the storage apparatus  22 , the communication apparatus  23 , the input apparatus  24  and the output apparatus  25  may be interconnected through a data bus  26 . 
     The arithmetic apparatus  21  includes at least one of a CPU (Central Processing Unit), a GPU (Graphic Processing Unit) and a FPGA (Field Programmable Gate Array), for example. The arithmetic apparatus  21  reads a computer program. For example, the arithmetic apparatus  21  may read a computer program that is stored in the storage apparatus  22 . For example, the arithmetic apparatus  21  may read a computer program that is stored in a non-transitory computer-readable recording medium by using a non-illustrated recording medium reading apparatus of the key point extraction apparatus  2 . The arithmetic apparatus  21  may obtain (namely, download or read) a computer program from a non-illustrated apparatus that is placed outside the key point extraction apparatus  2  through the communication apparatus  23  (alternatively, other communication apparatus) The arithmetic apparatus  21  executes the read computer program. As a result, a logical functional block for performing an operation (for example, the above described key point extraction operation) that should be performed by the key point extraction apparatus  2  is implemented in the arithmetic apparatus  21 . Namely, the arithmetic apparatus  21  is configured to serve as a controller for implementing the logical functional block for performing the operation (in other words, a processing) that should be performed by the key point extraction apparatus  2 . 
       FIG.  2    illustrates one example of the logical functional block that is implemented in the arithmetic apparatus  21  for performing the key point extraction operation. As illustrated in  FIG.  2   , in the arithmetic apparatus  21 , an image reduction unit  211  that is one specific example of “a reducing unit”, a key point extraction unit  212  that is one specific example of “a first extracting unit”, a target area set unit  213  that is one specific example of “a setting unit” and a key point extraction unit  214  that is one specific example of “a second extracting unit” are implemented. Note that a detail of an operation of each of the image reduction unit  211 , the key point extraction unit  212 , the target area set unit  213  and the key point extraction unit  214  will be described later in detail, however, a summary thereof will be described briefly here. The image reduction unit  211  is configured to generate a reduction image IMG 2  by reducing the person image IMG 1 . The key point extracting unit  212  is configured to extract the key point KP of the target object (the iris in the first example embodiment) that is included in the reduction image IMG 2  from the reduction image IMG 2 . The target area set unit  213  is configured to set a target area TA that designates a part of the person image IMG 1  based on the key point extracted by the key point extraction unit  212 . The key point extracting unit  214  is configured to extract the key point KP of the target object (the iris in the first example embodiment) that is included in a target image IMG 1 _TA from the target image IMG 1 _TA of the person image IMG 1  that is included in the target area TA set by the target area set unit  213 . 
     The storage apparatus  22  is configured to store a desired data. For example, the storage apparatus  22  may temporarily store the computer program that is executed by the arithmetic apparatus  21 . The storage apparatus  22  may temporarily store a data that is temporarily used by the arithmetic apparatus  21  when the arithmetic apparatus  21  executes the computer program. The storage apparatus  22  may store a data that is stored for a long term by the key point extraction apparatus  2 . Note that the storage apparatus  22  may include at least one of a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk apparatus, a magneto-optical disc, a SSD (Solid State Drive) and a disk array apparatus. Namely, the storage apparatus  22  may include a non-transitory recording medium. 
     The communication apparatus  23  is configured to communicate with the camera  1  through the communication network  3 . In the first example embodiment, the communication apparatus  23  receives the person image IMG 1  from the camera  1  through the communication network  3 . 
     The input apparatus  24  is an apparatus that receives an input of an information from an outside of the key point extraction apparatus  2  to the key point extraction apparatus  2 . For example, the input apparatus  24  may include an operational apparatus (for example, at least one of a keyboard, a mouse and a touch panel) that is operable by an operator of the key point extraction apparatus  2 . For example, the input apparatus  24  may include a reading apparatus that is configured to read an information recorded as a data in a recording medium that is attachable to the key point extraction apparatus  2 . 
     The output apparatus  25  is an apparatus that outputs an information to an outside of the key point extraction apparatus  2 . For example, the output apparatus  25  may output the information as an image. Namely, the output apparatus  25  may include a display apparatus (what we call a display) that is configured to display the image representing the information to be outputted. For example, the output apparatus  25  may output the information as a sound. Namely, the output apparatus  25  may include an audio apparatus (what we call a speaker) that is configured to output the sound. For example, the output apparatus  25  may output the information on a paper. Namely, the output apparatus  25  may include a print apparatus (what we call a printer) that is configured to print a desired information on the paper. 
     (1-3) Flow of Key Point Extraction Operation performed by Key Point Extraction Apparatus  2   
     Next, with reference to  FIG.  3   , a flow of the key point extraction operation that is performed by the key point extraction apparatus  2  in the first example embodiment will be described.  FIG.  3    is a flowchart that illustrates the flow of the key point extraction operation that is performed by the key point extraction apparatus  2  in the first example embodiment. 
     As illustrated in  FIG.  3   , the key point extraction apparatus  2  obtains the person image IMG 1  from the camera  1  (a step S 11 ). Specifically, the key point extraction apparatus  2  receives the person image IMG 1 , which is transmitted to the key point extraction apparatus  2  by the camera  1 , by using the communication apparatus  23  through the communication network  3 . 
     Then, the image reduction unit  211  reduces the person image IMG 1  obtained at the step S 11  (a step S 12 ). As a result, the image reduction unit  211  generates the reduction image IMG 2  that is the reduced person image IMG 1  (the step S 12 ). 
     An operation for reducing the person image IMG 1  may mean an operation for compressing the person image IMG 1 . The operation for reducing the person image IMG 1  may mean an operation for reducing a data size of the person image IMG 1 . The operation for reducing a data size of the person image IMG 1  may mean an operation fir reducing the number of pixels of the person image IMG 1 . For example, the operation for reducing the data size of the person image IMG 1  to be ⅕ times may mean the operation fir reducing the number of pixels of the person image IMG 1  to be ⅕ times. 
     The image reduction unit  211  may reduce the person image IMG 1  at a desired reduction rate. The desired reduction rate may be a fixed value that is determined in advance. The desired reduction rate may be variable. For example, the key point extraction apparatus  2  may change the reduction rate. For example, the operator of the key point extraction apparatus  2  may change the reduction rate. 
     The image reduction unit  211  may reduce the person image IMG 1  by using any image reduction method for reducing the image. For example, the mage reduction unit  211  may reduce the person image IMG 1  by using a bicubic method. For example, the mage reduction unit  211  may reduce the person image IMG 1  by using a bilinear method. For example, the mage reduction unit  211  may reduce the person image IMG 1  by using a nearest neighbor method. 
     Then, the key point extraction unit  212  extracts the key point KP of the iris that is included in the reduction image IMG 2  from the reduction image IMG 2  generated at the step S 12  (a step S 13 ). 
     The key point KP may include a key point KP that corresponds to a point from which a characteristic part of the target object is determinable. Thus, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a point from which a characteristic part of the iris is determinable. For example, as illustrated in  FIG.  4    that illustrates one example of the key point KP of the iris extracted from the reduction image IMG 2 , the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP 1  that corresponds to a point from which an inner outline of the iris (namely, substantially, an outline of a pupil) is determinable. The key point KP 1  may be a point that is located on the inner outline of the iris. For example, as illustrated in  FIG.  4   , the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP 2  that corresponds to a point from which an outer outline of the iris is determinable. The key point KP 2  may be a point that is located on the outer outline of the iris. For example, as illustrated in  FIG.  4   , the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP 3  that corresponds to a point from which a center of the iris is determinable. The key point KP 3  may be a point that is located on the center of the iris. Note that the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a point from which a center of the pupil, which is located on the center of the iris, is determinable, in addition to or instead of the key point KP 3  that corresponds to the point from which the center of the iris is determinable. For example, as illustrated in  FIG.  4   , the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP 4  that corresponds to a point from which an edge of an eyelid that is likely to hide the iris partially is determinable. The key point KP 4  may be a point that is located on the edge of the eyelid. For example, as illustrated in  FIG.  4   , the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP 5  that corresponds to a point from which an eye including the iris is determinable. As one example, the key point extraction unit  212  may extract, as the key point KP 5 , at least one of a key point KP 5 - 1  that corresponds to a point from which an inner corner of the eye is determinable and a key point KP 5 - 2  that corresponds to a point from which an outer corner of the eye is determinable. 
     The key point KP may include a key point KP that corresponds to a line from which the characteristic part of the target object is determinable in addition to or instead of the key point KP that corresponds to the point from which the characteristic part of the target object is determinable. Thus, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line from which the characteristic part of the iris is determinable. For example, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line from which the inner outline of the iris is determinable (for example, a line that extends along the inner outline of the iris). For example, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line from which the outer outline of the iris is determinable (for example, a line that extends along the outer outline of the iris). For example, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line from which the edge of the eyelid is determinable (for example, a line that extends along the edge of the eyelid). For example, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line that connects the outer corner of the eye and the inner corner of the eye. 
     At least one of the point and the line that is extracted as the key point KP may be usable to quantitatively determine the target object. Thus, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to at least one of the point and the line that is usable to quantitatively determine the iris. For example, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line that is usable to determine a size of the iris. As one example, when a shape of the iris is a circular shape, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line that is usable to determine a radius (for example, a diameter) of the iris that is one example of the size of the iris (for example, a line that passes through the center of the iris and both edges of which exist on the outer outline of the iris). As another example, when the shape of the iris is an oval shape, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line that is usable to determine at least one of a major diameter and a minor diameter of the iris that are examples of the size of the iris. The line that is usable to determine the major diameter of the iris may include a line that indicates a major axis of the iris, for example. The line that is usable to determine the minor diameter of the iris may include a line that indicates a minor axis of the iris, for example. Incidentally, when at least one of the line that indicates the major axis of the iris and the line that indicates the minor axis of the iris is determined, a rotational angle of the iris (namely, a rotational angle of an ellipse formed by the iris) is also determinable. Thus, when the shape of the iris is the oval shape, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds a line that is usable to determine the rotational angle of the iris (namely, the rotational angle of the ellipse formed by the iris). For example, the key point extraction unit  212  may extract, as the key point KP of the iris, a key point KP that corresponds to a line that is usable to determine a size (for example, a diameter) of the pupil that is located on the center of the iris. 
     The key point extraction unit  212  may extract the key point KP by using a neural network. Specifically, the key point extraction unit  212  may extract the key point KP by using a neural network that is configured to output the key point KP of the iris included in the reduction image IMG 2  (alternatively, any image including the person image IMG 1 ) when the reduction image IMG 2  (alternatively, any image including the person image IMG 1 ) is inputted thereto. It is preferable that a parameter of the neural network be learned by using a learning data that includes a learning image for learning the parameter of the neural network and a ground truth label of the key point KP of the iris included in the learning image (namely, a ground truth key point that is the key point KP that should be extracted from the learning image). Note that the neural network is one example of a learnable learning model. Thus, the key point extraction unit  212  may extract the key point KP by using any learning model that is different from the neural network. 
     An operation for extracting the key point KP may mean an operation for determining a position of the key point KP in the reduction image IMG 2  (for example, a position of the key point KP in the reduction image IMG 2  along each of a height direction and a width direction). In this case, the key point extraction unit  212  may determine the position of the key point KP in the reduction image IMG 2 . When the key point KP is extracted by using the neural network as described above, the neural network may output the position of the key point KP in the reduction image IMG 2 . 
     Again in  FIG.  3   , then, the target area set unit  213  sets the target area TA that designates a part of the person image IMG 1  based on the key point extracted at the step S 13  (namely, the key point KP in the reduction image IMG 2 ) (a step S 14 ). 
     The target area set unit  213  may determine a position in the person image IMG 1  that corresponds to the position of the key point KP in the reduction image IMG 2  and set the target area at a position in the person image IMG 1  that is determined based on the determined position. When a plurality of key points KP are extracted in the reduction image IMG 2 , the target area set unit  213  may determine a position in the person image IMG 1  that corresponds to at least one of the plurality of the key points KP and set the target area at a position in the person image IMG 1  that is determined based on the determined position. 
       FIG.  5    illustrates one example of the target area TA. As illustrated in  FIG.  5   , the target area set unit  213  may set, as the target area, an area that has a desired shape and that spreads from a position of the center of the iris in the person image IMG 1 . In this case, the target area set unit  213  may determine a position P 3  of the center of the iris in the person image IMG 1  based on the key point KP 3  that determines the center of the iris in the reduction image IMG 2 . For example, the target area set unit  213  may determine the position P 3  of the center of the iris in the person image IMG 1  by converting the position of the key point KP 3  that determines the center of the iris in the reduction image IMG 2  into a position in the person image IMG 1 . Then, the target area set unit  213  may set, as the target area, an area that has the desired shape and that spreads from the position P 3  of the center of the iris in the person image IMG 1 . Namely, the target area set unit  213  may set the target area at a position that spreads from the position of the center of the iris in the person image IMG 1 . 
     In an example illustrated in  FIG.  5   , the target area set unit  213  sets the target area TA that has a rectangular shape (namely, a square shape or an oblong shape). However, the target area set unit  213  may set the target area TA that has a shape that is different from the rectangular shape. For example, the target area set unit  213  may set the target area TA that has a circular shape. For example, the target area set unit  213  may set the target area TA that has an oval shape. For example, the target area set unit  213  may set the target area TA that has any polygonal shape. For example, the target area set unit  213  may set the target area TA that has any shape. Note that the target area set unit  213  sets the target area TA having a fixed size that is determined in advance, however, the target area set unit  213  may change a size of the target area TA as described in detail later as a modified example. 
     Again in  FIG.  3   , then, the target area set unit  213  extracts (namely, cuts), from the person image IMG 1 , the target image IMG 1 _TA of the person image IMG 1  that is included in the target area TA (a step S 15 ). 
     Here, the target area TA is set sometimes so that a part of the target area TA does not overlap with the person image IMG 1 . For example, when the target area TA that spreads from the position P 3  of the center of the iris and the size of which is N times as large as the diameter of the iris is set as described above, there is a possibility that a part of the target area TA does not overlap with the person image IMG 1  depending on the position of the iris in the person image IMG 1 . For example, as illustrated in  FIG.  6   , when the iris is near an edge of the person image IMG 1  in the person image IMG 1 , there is a possibility that a part of the target area TA does not overlap with the person image IMG 1  (for example, a part of the target area TA is outside the person image IMG 1 ). In this case, the target area set unit  213  may perform a padding processing for enlarging the person image IMG 1  by using padding data so that a part of the target area TA that is outside the person image IMG 1  overlaps with the padded person image IMG 1 . In this case, the target area set unit  213  may perform the padding processing so that an image part of the person image IMG 1  that is enlarged by the padding data overlaps with a part of the target area TA that is outside the person image IMG 1 . Note that any method may be used as a method for the padding processing. At least one of a duplicating method (a duplicate padding) and a reflection method (a reflection padding) is one example of the method for the padding processing. 
     Again in  FIG.  3   , then, the key point extraction unit  214  extracts the key point KP of the iris that is included in the target image IMG 1 _TA from the target image IMG 1 _TA extracted at the step S 15  (a step S 16 ). Namely, as illustrated in  FIG.  7   , the key point extraction unit  214  extracts the key point KP from the target image IMG 1 _TA that is a part of the person image IMG 1  instead of extracting the key point KP from whole of the person image IMG 1 . Even in this case, the iris is properly included in the target image IMG 1 _TA as illustrated in  FIG.  7   , because the target area TA is set based on the key point KP extracted from the reduction image IMG 2 . Conversely, the target area TA is set so that the iris is properly included in the target image IMG 1 _TA (specifically, so that the iris is properly included in the target image IMG 1 _TA to allow necessary key point KP to be extractable). Thus, even when the key point KP of the iris is extracted from the target image IMG 1 _TA, the key point extraction part  214  is capable of extracting the necessary key point KP properly (typically, without shortage), as with a case where the key point KP of the iris is extracted from whole of the person image IMG 1 . 
     Note that an operation for extracting the key point KP at the step S 16  may be same as the operation for extracting the key point KP at the step S 13 . Namely, the key point extraction unit  214  may extract the key point KP at the step S 16 , as with the key point extraction unit  212  that extracts the key point KP at the step S 13 . Thus, a detailed description of the operation for extracting the key point KP at the step S 16  is omitted. 
     The key point extraction unit  214  may determine a position of the key point KP in the target image IMG 1 _TA (namely, a position of the key point KP in the person image IMG 1 ), as with the key point extraction unit  212  that determines the position of the key point KP in the reduction image IMG 2 . In this case, the key point extraction unit  214  may determine the position itself (namely, an absolute position) of the key point KP in the person image IMG 1 . Alternatively, the key point extraction unit  214  may determine the relative position of the key point KP in the person image IMG 1  relative to the position of the key point KP in the reduction image IMG 2 . In this case, the key point extraction unit  214  may be regarded to determine a correction amount for correcting the position of the key point KP in the reduction image IMG 2  to the position of the key point KP in the person image IMG 1 . 
     Then, the key point KP extracted at the step S 16  may be used for a desired information processing (for example, an information processing relating to the above described iris authentication). 
     (1-4) Technical Effect of Key Point Extraction Apparatus  2   
     As described above, the key point extraction apparatus  2  in the first example embodiment extracts the key point KP from the target image IMG 1 _TA of the person image IMG 1  that is included in the target area TA. Thus, a time required for the key point extraction apparatus  2  to extract the key point KP from the target image IMG 1 _TA is shorter than a time required for extracting the key point KP from whole of the person image IMG 1 . Furthermore, although the key point extraction apparatus  2  extracts the key point KP from whole of the reduction image IMG 2  in order to set the target area TA, a time required for extracting the key point KP from whole of the reduction image IMG 2  is much shorter than the time required for extracting the key point KP from whole of the person image IMG 1 . Thus, the key point extraction apparatus  2  is capable of extracting the key point KP relatively rapidly. 
     Furthermore, since the person image IMG 1  is not a reduced image, the target image IMG 1 _TA is not a reduced image either. Thus, an accuracy of the key point KP extracted from the target image IMG 1 _TA is higher than that of the key point KP extracted from the reduction image IMG 2 . Specifically, a difference (for example, a difference of the position) between the key point KP extracted from the target image IMG 1 _TA and an actual key point KP is smaller than a difference between the key point KP extracted from the reduction image IMG 2  and the actual key point KR Thus, the key point extraction apparatus  2  is capable of extracting the key point KP accurately. 
     As described above, the key point extraction apparatus  2  is capable of extracting the key point KP relatively rapidly and extracting the key point KP accurately. Namely, the key point extraction apparatus  2  is capable of achieving both of a reduction of the time required for extracting the key point KP and an improvement of the accuracy of the extracted key point KP. 
     Incidentally, a key point extraction apparatus in a first comparison example that merely extracts the key point KP from the reduction image IMG 2  without setting the target area TA has a technical problem that the accuracy of the extracted key point KP is low, although it is capable of extracting the key point KP relatively rapidly. On the other hand, a key point extraction apparatus in a second comparison example that merely extracts the key point KP from whole of the person image IMG 1  without setting the target area TA has a technical problem that it is not capable of extracting the key point KP relatively rapidly, although the accuracy of the extracted key point KP is high. Namely, both of the key point extraction apparatus in the first comparison example and the key point extraction apparatus in the second comparison example has a technical problem that they are not capable of achieving both of the reduction of the time required for extracting the key point KP and the improvement of the accuracy of the extracted key point KP. However, the key point extraction apparatus  2  in the first example embodiment is capable of achieving both of the reduction of the time required for extracting the key point KP and the improvement of the accuracy of the extracted key point KP. Therefore, the key point extraction apparatus  2  in the first example embodiment is capable of solving the technical problem of the key point extraction apparatus in the first comparison example and the key point extraction apparatus in the second comparison example. 
     (1-5) Modified Example of Key Point Extraction Apparatus  2   
     (1-5-1) First Modified Example 
     In the above described description, the key point extraction apparatus  2  includes the key point extraction unit  212  that is configured to extract the key point KP from the reduction image IMG 2  and the key point extraction unit  214  that is configured to extract the key point KP from the target image IMG 1 _TA separately. However, the key point extraction apparatus  2  may include a single key point extraction unit that is configured to extract the key point KP from each of the reduction image IMG 2  and the target image IMG 1 _TA, in addition to or instead of the key point extraction units  212  and  214 . 
     (1-5-2) Second Modified Example 
     In the above described description, the target area set unit  213  sets the target area TA having a fixed size that is determined in advance. However, the target area set unit  213  may change the size of the target area TA if needed. Namely, the size of the target area TA may be variable. Incidentally, when the shape of the target area TA is the rectangular shape, the size of the target area TA may include at least one of a size of the target area TA in the height direction and a size of the target area TA in the width direction. When the shape of the target area TA is the circular shape, the size of the target area TA may include a radius (for example, a diameter) of the target area TA. When the shape of the target area TA is the oval shape, the size of the target area TA may include at least one of a major diameter and a minor diameter of the target area TA. 
     Next, a specific example of an operation for changing the size of the target area TA will be described. Note that the target area set unit  213  may not perform all of below described operations when the size of the target area TA is changed. The target area set unit  213  may selectively perform a part of the below described operations when the size of the target area TA is changed. 
     The target area set unit  213  may change the size of the target area TA based on the key point KP in the reduction image IMG 2 . 
     As one example, when the key point KP that is usable to determine the radius (for example, the diameter) of the iris (namely, from which the radius (for example, the diameter) is determinable) is extracted as described above, the target area set unit  213  may change the size of the target area TA so that the size of the target area TA is N times as large as the diameter of the iris. A scaling factor N may be larger than 1, for example. for example, when the scaling factor N is 2 in an example illustrated in  FIG.  5   , the size of the target area TA in the height direction (the size in a vertical direction in  FIG.  5   ) may be twice as large as the diameter of the iris, and the size of the target area TA in the width direction (the size in a horizontal direction in  FIG.  5   ) may be twice as large as the diameter of the iris. 
     As another example, when the key point KP from which the edge of the eyelid is determinable is extracted as described above, the target area set unit  213  may change the size of the target area TA in the height direction based on the position of the eyelid. Specifically, for example, the target area set unit  213  may change the size of the target area TA so that at least one of two sides of the target area TA that face with each other along the height direction (two sides that face with each other along the vertical direction in  FIG.  5   ) is closer to the edge of the eyelid. For example, the target area set unit  213  may change the size of the target area TA so that an upper side of the two sides of the target area TA that face with each other along the height direction is closer to an edge of an upper eyelid, for example. For example, the target area set unit  213  may change the size of the target area TA so that a lower side of the two sides of the target area TA that face with each other along the height direction is closer to an edge of a lower eyelid, for example. 
     Note that the target area TA may be referred to as a “surrounding area”, because it is typically set to include the iris and an image part around the iris. 
     In this manner, in the second modified example, the key point extraction apparatus  2  is configured to change the size of the target area TA. Thus, there is a lower possibility that the size of the target area TA set by the key point extraction apparatus  2  is larger than necessary, compared to a case where the size of the target area TA is fixed (namely, is not allowed to be changed). Thus, there is a low possibility that the target image IMG 1 _TA that is used to extract the key point KP is larger than necessary. Thus, the key point extraction apparatus  2  is capable of extracting the key point KP included in the person image IMG 1  relatively rapidly. Furthermore, there is also a lower possibility that the size of the target area TA set by the key point extraction apparatus  2  is smaller than necessary. Thus, there is a low possibility that a situation in which the necessary key point KP cannot be extracted from the target image IMG 1 _TA is caused due to a part of the iris not being included in the target area TA. Thus, the key point extraction apparatus  2  is capable of extracting the key point KP included in the person image IMG 1  properly (typically, without shortage). 
     Moreover, in the second modified example, the key point extraction apparatus  2  is configured to change the size of the target area TA based on the key point KP extracted from the reduction image IMG 2 . The key point extraction apparatus  2  is capable of changing the size of the target area TA based on an information relating to the actual iris, because the key point KP extracted from the reduction image IMG 2  includes an information relating to the iris. Thus, there is much lower possibility that the size of the target area TA set by the key point extraction apparatus  2  is larger or smaller than necessary, compared to a case where the size of the target area TA is changed without using the key point KP extracted from the reduction image IMG 2 . Thus, the key point extraction apparatus  2  is capable of extracting the key point KP included in the person image IMG 1  relatively rapidly and properly (typically, without shortage). 
     Moreover, in the second modified example, the key point extraction apparatus  2  is configured to change the size of the target area TA to be a size based on the size of the iris. Thus, there is much lower possibility that the size of the target area TA set by the key point extraction apparatus  2  is larger or smaller than necessary, compared to a case where the size of the target area TA is changed without considering the size of the iris. Thus, the key point extraction apparatus  2  is capable of extracting the key point KP included in the person image IMG 1  relatively rapidly and properly (typically, without shortage). 
     (2) Key Point Extraction System SYS in Second Example Embodiment 
     Next, the key point extraction system SYS in a second example embodiment will be described. Note that the key point extraction system SYS in the second example embodiment is referred to as a “key point extraction system SYSb” in the below described description. 
     The key point extraction system SYSb in the second example embodiment is different from the above described key point extraction system SYSa in the first example embodiment in that it includes a key point extraction apparatus  2   b  instead of the key point extraction apparatus  2 . Another feature of the key point extraction system SYSb may be same as another feature of the key point extraction system SYSa. Thus, in the below describe description, the key point extraction apparatus  2   b  in the second example embodiment will be mainly described. Note that a detailed description of the component that is already described is omitted by assigning the same reference number thereto. Moreover, a detailed description of a process that is already described is omitted by assigning the same step number thereto. 
     (2-1) Configuration of Key Point Extraction Apparatus  2   b    
     Firstly, with reference to  FIG.  8   , a configuration of the key point extraction apparatus  2   b  in the second example embodiment will be described.  FIG.  8    is a block diagram that illustrates the configuration of the key point extraction apparatus  2   b  in the second example embodiment. 
     As illustrated in  FIG.  8   , the key point extraction apparatus  2   b  in the second example embodiment is different from the key point extraction apparatus  2  in the first example embodiment in that the logical function block that is implemented in the arithmetic apparatus  21  of the key point extraction apparatus  2   b  in order to perform the key point extraction operation is different from the logical function block that is implemented in the arithmetic apparatus  21  of the key point extraction apparatus  2 . Another feature of the key point extraction apparatus  2   b  may be same as another feature of the key point extraction apparatus  2 . 
     As illustrated in  FIG.  8   , in the second example embodiment, a key point extraction unit  215  that is one specific example of a “third extracting unit”, an image conversion unit  216  that is one specific example of a “image converting unit” and a key point extraction unit  217  are implemented in the arithmetic apparatus  21 . Note that a detail of an operation of each of the key point extraction unit  215 , the image conversion unit  216  and the key point extraction unit  217  will be described later in detail, however, a summary thereof will be described briefly here. The key point extracting unit  215  is configured to extract the key point KP of the target object (the iris in the second example embodiment) that is included in the person image IMG 1  from the person image IMG 1 . The image conversion unit  216  is configured to generate a conversion image IMG 3  by performing an image conversion processing that converts the person image IMG 1  based on the key point KP extracted by the key point extraction unit  215 . The key point extracting unit  217  is configured to extract the key point KP of the target object (the iris in the second example embodiment) that is included in the conversion image IMG 3  from the conversion image IMG 3 . 
     (2-2) Flow of Key Point Extraction Operation performed by Key Point Extraction Apparatus  2   b    
     Next, with reference to  FIG.  9   , a flow of the key point extraction operation that is performed by the key point extraction apparatus  2   b  in the second example embodiment will be described.  FIG.  9    is a flowchart that illustrates the flow of the key point extraction operation that is performed by the key point extraction apparatus  2   b  in the second example embodiment. 
     As illustrated in  FIG.  9   , the key point extraction apparatus  2   b  obtains the person image IMG 1  from the camera  1  (the step S 11 ). 
     Then, the key point extracting unit  215  extracts the key point KP of the iris that is included in the person image IMG 1  from the person image IMG 1  obtained at the step S 11  (a step S 21 ). Note that an operation for extracting the key point KP at the step S 21  may be same as the operation for extracting the key point KP at at least one of the step S 13  and the step S 16  in  FIG.  3   . Namely, the key point extraction unit  215  may extract the key point KP at the step S 21 , as with at least one of the key point extraction unit  212  that extracts the key point KP at the step S 13  and the key point extraction unit  214  that extracts the key point KP at the step S 16 . Thus, a detailed description of the operation for extracting the key point KP at the step S 21  is omitted. 
     Then, the image conversion unit  216  performs the image conversion processing that convers the person image IMG 1  based on the key point KP extracted at the step S 21  (a step S 22 ). As a result, the image conversion unit  216  generates the conversion image IMG 3  that is the person image IMG 1  on which the image conversion processing has been performed (the step S 22 ). 
     The image conversion processing at the step S 22  may include or may not include a processing for changing a characteristic of the iris included in the person image IMG 1 . The image conversion processing at the step S 22  may include or may not include a processing for normalizing the characteristic of the iris included in the person image IMG 1 . The characteristic of the iris may include or may not include the size (for example, the diameter) of the iris. The characteristic of the iris may include the position of the iris. The characteristic of the iris may include or may not include a direction (in other words, an angle, an angle between horizontal line and a line that connects the inner corner of the eye and the outer corner of the eye, for example) of the iris. 
     Alternatively, the image conversion processing at the step S 22  may include or may not include a processing for changing a characteristic of the person image IMG 1  in addition to or instead of the processing for changing the characteristic of the iris included in the person image IMG 1 . The image conversion processing at the step S 22  may include or may not include a processing for normalizing the characteristic of the person image IMG 1 . 
     When a plurality of person images IMG 1  are converted to a plurality of conversion images IMG 3 , respectively, the image conversion processing at the step S 22  may include or may not include a processing for reducing a variability between the characteristics of a plurality of irises that are included in the plurality of conversion images IMG 3 , respectively. Namely, the image conversion processing at the step S 22  may include or may not include a processing for allowing the variability between the characteristics of the plurality of irises that are included in the plurality of conversion images IMG 3 , respectively, is smaller than a variability between the characteristics of the plurality of irises that are included in the plurality of person images IMG 1 , respectively. 
     Under the assumption that the plurality of person images IMG 1  are converted to the plurality of conversion images IMG 3 , respectively, the image conversion processing at the step S 22  may include or may not include a processing for reducing a variability between the characteristics of the plurality of conversion images IMG 3 . Namely, the image conversion processing at the step S 22  may include or may not include a processing for allowing the variability between the characteristics of the plurality of conversion images IMG 3  is smaller than a variability between the characteristics of the plurality of person images IMG 1 . 
     Then, the key point extracting unit  217  extracts the key point KP of the iris that is included in the conversion image IMG 3  from the conversion image IMG 3  generated at the step S 22  (a step S 23 ). Note that an operation for extracting the key point KP at the step S 23  may be same as the operation for extracting the key point KP at the step S 21 . Namely, the key point extraction unit  217  may extract the key point KP at the step S 23 , as with the key point extraction unit  215  that extracts the key point KP at the step S 21 . Thus, a detailed description of the operation for extracting the key point KP at the step S 23  is omitted. 
     (2-3) Technical Effect of Key Point Extraction Apparatus  2   b    
     As described above, the key point extraction apparatus  2   b  in the second example embodiment generates the conversion image IMG 3  by performing the image conversion processing that converts the person image IMG 1  based on the key point KP extracted from the person image IMG 1 , and extracts the key point KP from the conversion image IMG 3 . Thus, the key point extraction apparatus  2   b  is capable of extracting the key point KP from the conversion image IMG 3  in which the iris is included in a desired aspect. Thus, the key point extraction apparatus  2   b  is capable of extracting the key point KP more accurately, compared to a key point extraction apparatus in a third comparison example that extracts the key point KP from the person image IMG 1  in which the iris is not necessarily included in the desired aspect. 
     (2-4) Modified Example of Key Point Extraction Apparatus  2   b    
     (2-4-1) First Modified Example 
     The image conversion processing at the step S 22  in  FIG.  9    may include a processing for performing a geometric transformation on the person image IMG 1 . As one example, the image conversion processing at the step S 22  may include a processing for performing an affine transformation on the person image IMG 1 . Namely, the image conversion processing at the step S 22  may include at least one of a translation processing for translating the person image IMG 1  along at least one of the vertical direction and the width direction, a rotation processing for rotating the person image IMG 1  and a scaling processing for scaling the person image IMG 1 . Next, with reference to  FIG.  10    to  FIG.  12   , one example of each of the translation processing for translating the person image IMG 1 , the rotation processing for rotating the person image IMG 1  and the scaling processing for scaling the person image IMG 1  will be describe. 
       FIG.  10    conceptually illustrates the translation processing for translating the person image IMG 1 . As illustrated in  FIG.  10   , the image conversion unit  216  may translate the iris included in the person image IMG 1  (namely, may change the position of the iris) by translating the person image IMG 1 . For example, the image conversion unit  216  may translate the person image IMG 1  based on the key point KP 3  from which the center of the iris is determinable so that the center of the iris is closer to a center of the person image IMG 1 . As a result, a distance between the center of the iris and a center of the conversion image IMG 3  in the conversion image IMG 3  is shorter than a distance between the center of the iris and a center of the person image IMG 1  in the person image IMG 1  on which the image conversion processing is not performed yet. In this case, the image conversion unit  216  may translate the person image IMG 1  based on the key point KP 3  from which the center of the iris is determinable so that the center of the iris is located at the center of the person image IMG 1 . As a result, the center of the iris, which is not located at the center of the person image IMG 1  before the image conversion processing is performed, may be located at the center of the conversion image IMG 3 . 
     In this case, when the plurality of person images IMG 1  are converted to the plurality of conversion images IMG 3 , respectively, the position of the center of the iris included in the conversion image IMG 3  is approximately the same among the plurality of conversion images IMG 3 . Here, when the key point extraction apparatus  2   b  extracts the key point KP of the iris from each of the plurality of conversion images IMG 3  among which the position of the center of the iris varies largely, there is a possibility that the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from the conversion image IMG 3  in which the center of the iris is located at a first position and is not capable of properly extracting the key point KP from the conversion image IMG 3  in which the center of the iris is located at a second position that is different from the first position, due to a variability of the position of the center of the iris. However, in the first modified example, the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from each of the plurality of conversion images IMG 3 , because the position of the center of the iris is approximately the same among the plurality of conversion images IMG 3 . 
       FIG.  11    conceptually illustrates the rotation processing for rotating the person image IMG 1 . As illustrated in  FIG.  11   , the image conversion unit  216  may rotate the iris included in the person image IMG 1  (namely, may change the direction of the iris) by rotating the person image IMG 1 . For example, the image conversion unit  216  may rotate the person image IMG 1  based on the key point KP 5 - 1  from which the inner corner of the eye is determinable and the key point KP 5 - 2  from which the outer corner of the eye is determinable (alternatively, the key point KP from which the line that connects the outer corner of the eye and the inner corner of the eye is determinable) so that the line that connects the outer corner of the eye and the inner corner of the eye is closer to be horizontal in the person image IMG 1 . As a result, the line that connects the outer corner of the eye and the inner corner of the eye in the conversion image IMG 3  is closer to be horizontal than the line that connects the outer corner of the eye and the inner corner of the eye in the person image IMG 1 . In this case, the image conversion unit  216  may rotate the person image IMG 1  so that the line that connects the outer corner of the eye and the inner corner of the eye is horizontal. As a result, the line that connects the outer corner of the eye and the inner corner of the eye, which is not horizontal before the image conversion processing is performed, may be horizontal in the conversion image IMG 3 . 
     In this case, when the plurality of person images IMG 1  are converted to the plurality of conversion images IMG 3 , respectively, the direction of the iris (here, a direction along which the line that connects the outer corner of the eye and the inner corner of the eye extends) included in the conversion image IMG 3  is approximately the same among the plurality of conversion images IMG 3 . Here, when the key point extraction apparatus  2   b  extracts the key point KP of the iris from each of the plurality of conversion images IMG 3  among which the direction of the iris varies largely, there is a possibility that the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from the conversion image IMG 3  in which the direction of the iris is a first direction (for example, in which the line that connects the outer corner of the eye and the inner corner of the eye is close to the horizontal direction) and is not capable of properly extracting the key point KP from the conversion image IMG 3  in which the direction of the iris is a second direction that is different from the first direction (for example, in which the line that connects the outer corner of the eye and the inner corner of the eye is largely different from the horizontal direction), due to a variability of the direction of the iris. However, in the first modified example, the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from each of the plurality of conversion images IMG 3 , because the direction of the iris is approximately the same among the plurality of conversion images IMG 3 . 
       FIG.  12    conceptually illustrates the scaling processing for scaling the person image IMG 1 . As illustrated in  FIG.  12   , the image conversion unit  216  may scale the iris included in the person image IMG 1  (namely, may change the size of the iris) by scaling the person image IMG 1 . For example, the image conversion unit  216  may scale the person image IMG 1  based on the key point KP 2  from which the outer outline of the iris is determinable (alternatively, the key point KP that is usable to determine the size of the iris) so that the size of the iris in the person image IMG 1  is closer to a predetermined size. As a result, a difference between the predetermined size and the size of the iris in the conversion image IMG 3  is smaller than a difference between the predetermined size and the size of the iris in the person image IMG 1 . In this case, the image conversion unit  216  may scale the person image IMG 1  so that the size of the iris in the person image IMG 1  becomes the predetermined size. As a result, the size of the iris, which is not the predetermined size before the image conversion processing is performed, may become the predetermined size. Note that the processing for scaling the person image IMG 1  so that the size of the iris becomes the predetermined size may be regarded to be a processing for normalizing the size of the iris. 
     In this case, when the plurality of person images IMG 1  are converted to the plurality of conversion images IMG 3 , respectively, the size of the iris included in the conversion image IMG 3  is approximately the same among the plurality of conversion images IMG 3 . Here, when the key point extraction apparatus  2   b  extracts the key point KP of the iris from each of the plurality of conversion images IMG 3  among which the size of the iris varies largely, there is a possibility that the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from the conversion image IMG 3  in which the size of the iris is a first size and is not capable of properly extracting the key point KP from the conversion image IMG 3  in which the size of the iris is a second size that is different from the first size, due to a variability of the size of the iris. However, in the first modified example, the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from each of the plurality of conversion images IMG 3 , because the size of the iris is approximately the same among the plurality of conversion images IMG 3 . 
     (2-4-2) Second Modified Example 
     As described above, the image conversion processing at the step S 22  in  FIG.  9    may include the processing for changing the characteristic of the person image IMG 1 . In the second modified example, the characteristic of the person image IMG 1  may include a brightness of the person image IMG 1 . Especially, the characteristic of the person image IMG 1  may include a brightness of an image part of the person image IMG 1  that corresponds to the iris. In this case, the image conversion processing at the step S 22  may include, as the processing for normalizing the brightness of the person image IMG 1 , a processing for setting a maximum brightness and a minimum brightness of the person image IMG 1  to be a predetermined brightness upper limit value and a brightness lower limit value, respectively. 
     In this case, when the plurality of person images IMG 1  are converted to the plurality of conversion images IMG 3 , respectively, a range of the brightness (namely, a range from the maximum brightness to the minimum brightness) of the conversion image IMG 3  is approximately the same. For example, a range of the brightness (namely, a range from the maximum brightness to the minimum brightness) of the image part of the conversion image IMG 3  that corresponds to the iris is approximately the same. Here, when the key point extraction apparatus  2   b  extracts the key point KP of the iris from each of the plurality of conversion images IMG 3  among which the range of the brightness varies largely, there is a possibility that the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from the conversion image IMG 3  the brightness of which is within a first range and is not capable of properly extracting the key point KP from the conversion image IMG 3  the brightness of which is within a second range that is different from the first range, due to a variability of the range of the brightness. However, in the second modified example, the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from each of the plurality of conversion images IMG 3 , because the range of the brightness is approximately the same among the plurality of conversion images IMG 3 . 
     (2-4-3) Other Modified Example 
     The key point extraction apparatus  2   b  may perform an operation for extracting the key point KP from the conversion image IMG 3  after generating the conversion image IMG 3  and generating (in this case, re-generating) new conversion image IMG 3  by performing an image conversion processing that converts the conversion image IMG 3  based on the extracted key point KP. Namely, the key point extraction apparatus  2   b  may perform the operation from the step S 21  to the step S 22  in  FIG.  9    at least one time by using the generated conversion image IMG 3  after generating the conversion image IMG 3  at the step S 22  in  FIG.  9   . The key point extraction apparatus  2   b  may repeat the operation from the step S 21  to the step S 22  in  FIG.  9    two or more times by using the generated conversion image IMG 3  after generating the conversion image IMG 3  at the step S 22  in  FIG.  9   . In this case, there is a high possibility that the iris is included in the conversion image IMG 3  in the desired aspect. For example, there is a high possibility that the center of the iris is located at the center of the conversion image IMG 3 , the line that connects the outer corner of the eye and the inner corner of the eye is horizontal, the size of the iris is the predetermined size and/or the maximum brightness and the minimum brightness become the brightness upper limit value and the brightness lower limit value, respectively. As a result, the key point extraction apparatus  2   b  is capable of properly extracting the key point KP from the conversion image IMG 3  in which the iris is included in the desired aspect. 
     The key point KP that is extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9    is mainly used by the image conversion unit  216  to perform the image conversion processing. In this case, the accuracy of the key point KP is not necessarily high. Thus, in the step S 21  in  FIG.  9   , the key point extraction unit  215  may extract the key point KP from the image (namely, the reduction image IMG 2 ) that is obtained by reducing the person image IMG 1  instead of the person image IMG 1 . 
     A type of the key point KP that is extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9    may be same as a type of the key point KP that is extracted by the key point extraction unit  217  at the step S 23  in  FIG.  9   . 
     Alternatively, the type of the key point KP that is extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9    may be partially different from the type of the key point KP that is extracted by the key point extraction unit  217  at the step S 23  in  FIG.  9   . For example, at the step S 21  in  FIG.  9   , the key point extraction unit  215  may extract at least the key point KP the type of which is necessary for the image conversion unit  216  to perform the image conversion processing. As one example, at the step S 21  in  FIG.  9   , the key point extraction unit  215  may extract the key point KP 3  from which the center of the iris is determinable and which is necessary for performing the above described translation processing. As another example, at the step S 21  in  FIG.  9   , the key point extraction unit  215  may extract the key point KP 5 - 1  from which the inner corner of the eye is determinable and the key point KP 5 - 2  from which the outer corner of the eye is determinable (alternatively, the key point KP from which the line that connects the outer corner of the eye and the inner corner of the eye is determinable) and which are necessary for performing the above described rotation processing. As another example, at the step S 21  in  FIG.  9   , the key point extraction unit  215  may extract the key point KP from which the size of the iris is determinable and which is necessary for performing the above described scaling processing. However, at the step S 21  in  FIG.  9   , the key point extraction unit  215  may extract the key point KP the type of which is not always necessary for the image conversion unit  216  to perform the image conversion processing. On the other hand, at the step S 23  in  FIG.  9   , the key point extraction unit  217  may extract the key point KP that is not extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9   . Alternatively, at the step S 23  in  FIG.  9   , the key point extraction unit  217  may extract the key point KP that is already extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9    in addition to or instead of the key point KP that is not extracted by the key point extraction unit  215 . 
     Alternatively, considering that the conversion image IMG 3  is generated by performing the image conversion processing on the person image IMG 1 , the key point KP that is extracted by the key point extraction unit  217  at the step S 23  in  FIG.  9    is approximately same as a key point that is obtained by a coordinate transformation, which is based on the image conversion processing, on the key point KP that is extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9   . Thus, at the step S 23  in  FIG.  9   , the key point extraction unit  217  may extract (in this case, calculate) the key point KP by performing the coordinate transformation, which is based on the image conversion processing, on the key point KP that is extracted by the key point extraction unit  215  at the step S 21  in  FIG.  9   . 
     In the above described description, the key point extraction apparatus  2   b  includes the key point extraction unit  215  that is configured to extract the key point KP from the person image IMG 1  and the key point extraction unit  217  that is configured to extract the key point KP from the conversion image IMG 3  separately. However, the key point extraction apparatus  2  may include a single key point extraction unit that is configured to extract the key point KP from each of the person image IMG 1  and the conversion image IMG 3 , in addition to or instead of the key point extraction units  215  and  217 . 
     (3) Key Point Extraction System SYS in Third Example Embodiment 
     Next, the key point extraction system SYS in a third example embodiment will be described. Note that the key point extraction system SYS in the third example embodiment is referred to as a “key point extraction system SYSc” in the below described description. 
     The key point extraction system SYSc in the third example embodiment is different from the above described key point extraction system SYSa in the first example embodiment in that it includes a key point extraction apparatus  2   c  instead of the key point extraction apparatus  2 . Another feature of the key point extraction system SYSc may be same as another feature of the key point extraction system SYSa. Thus, in the below describe description, the key point extraction apparatus  2   c  in the third example embodiment will be mainly described. 
     (3-1) Configuration of Key Point Extraction Apparatus  2   c    
     Firstly, with reference to  FIG.  13   , a configuration of the key point extraction apparatus  2   c  in the third example embodiment will be described.  FIG.  13    is a block diagram that illustrates the configuration of the key point extraction apparatus  2   c  in the third example embodiment. 
     As illustrated in  FIG.  13   , the key point extraction apparatus  2   c  in the third example embodiment is different from the key point extraction apparatus  2  in the first example embodiment in that the logical function block that is implemented in the arithmetic apparatus  21  of the key point extraction apparatus  2   c  in order to perform the key point extraction operation is different from the logical function block that is implemented in the arithmetic apparatus  21  of the key point extraction apparatus  2 . Another feature of the key point extraction apparatus  2   c  may be same as another feature of the key point extraction apparatus  2 . 
     As illustrated in  FIG.  13   , in the third example embodiment, not only the image reduction unit  211 , the key point extraction unit  212 , the target area set unit  213  and the key point extraction unit  214  that are described in the first example embodiment but also the key point extraction unit  215 , the image conversion unit  216  that are described in the second example embodiment are implemented in the arithmetic apparatus  21 . Namely, the key point extraction apparatus  2   c  in the third example embodiment may be a combination of the key point extraction apparatus  2  in the first example embodiment and the key point extraction apparatus  2   b  in the second example embodiment. 
     (3-2) Flow of Key Point Extraction Operation performed by Key Point Extraction Apparatus  2   c    
     Next, with reference to  FIG.  14   , a flow of the key point extraction operation that is performed by the key point extraction apparatus  2   c  in the third example embodiment will be described.  FIG.  14    is a flowchart that illustrates the flow of the key point extraction operation that is performed by the key point extraction apparatus  2   c  in the third example embodiment. 
     As illustrated in  FIG.  14   , the key point extraction apparatus  2   c  firstly performs a part of the key point extraction operation in the second example embodiment (the step S 11  to the step S 22 ). Specifically, the key point extraction apparatus  2   c  obtains the person image IMG 1  from the camera  1  (the step S 11 ). Then, the key point extracting unit  215  extracts the key point KP of the iris that is included in the person image IMG 1  from the person image IMG 1  obtained at the step S 11  (the step S 21 ). Then, the image conversion unit  216  generates the conversion image IMG 3  by performing the image conversion processing that convers the person image IMG 1  based on the key point KP extracted at the step S 21  (the step S 22 ). 
     Then, the key point extraction apparatus  2   c  performs the key point KP in the first example embodiment by using the conversion image IMG 3  instead of the person image IMG 1  (the step S 12  to the step S 16 ). Specifically, the image reduction unit  211  reduces the conversion image IMG 3  generated at the step S 22  (the step S 12 ). Then, the key point extraction unit  212  extracts the key point KP from the reduction image IMG 2  generated at the step S 12  (the step S 13 ). Then, the target area set unit  213  sets the target area TA that designates a part of the conversion image IMG 3  based on the key point extracted at the step S 13  (the step S 14 ). Then, the target area set unit  213  extracts, as the target image IMG 1 _TA from the conversion image IMG 3 , an image part of the conversion image IMG 3  that is included in the target area TA (the step S 15 ). T hen, the key point extraction unit  214  extracts the key point KP from the target image IMG 1 _TA extracted at the step S 15  (the step S 16 ). 
     (3-3) Technical Effect of Key Point Extraction Apparatus  2   c    
     As described above, the key point extraction apparatus  2   c  in the third example embodiment performs the key point extraction operation in the first example embodiment after performing the key point extraction operation in the second example embodiment. Thus, the key point extraction apparatus  2   c  in the third example embodiment is capable of achieving an effect that is same as the effect achievable by the key point extraction apparatus  2  in the first example embodiment and an effect that is same as the effect achievable by the key point extraction apparatus  2   b  in the second example embodiment. 
     (3-4) Modified Example of Key Point Extraction Apparatus  2   c    
     In the above described description, the key point extraction apparatus  2   c  includes the key point extraction unit  212  that is configured to extract the key point KP from the reduction image IMG 2 , the key point extraction unit  214  that is configured to extract the key point KP from the target image IMG 1 _TA and the key point extraction unit  215  that is configured to extract the key point KP from the person image IMG 1  separately. However, the key point extraction apparatus  2  may include a single key point extraction unit that is configured to extract the key point KP from at least two of the person image IMG 1 , the reduction image IMG 2  and the target image IMG 1 _TA, in addition to or instead of at least two of the key point extraction units  212 ,  214  and  215 . 
     (4) Key Point Extraction System SYS in Fourth Example Embodiment 
     Next, the key point extraction system SYS in a fourth example embodiment will be described. Note that the key point extraction system SYS in the fourth example embodiment is referred to as a “key point extraction system SYSd” in the below described description. 
     The key point extraction system SYSd in the fourth example embodiment is different from the above described key point extraction system SYSb in the second example embodiment in that it includes a key point extraction apparatus  2   d  instead of the key point extraction apparatus  2   b.  Another feature of the key point extraction system SYSd may be same as another feature of the key point extraction system SYSb. Thus, in the below describe description, the key point extraction apparatus  2   d  in the fourth example embodiment will be mainly described. 
     (4-1) Configuration of Key Point Extraction Apparatus  2   d    
     Firstly, with reference to  FIG.  15   , a configuration of the key point extraction apparatus  2   d  in the fourth example embodiment will be described.  FIG.  15    is a block diagram that illustrates the configuration of the key point extraction apparatus  2   d  in the fourth example embodiment. 
     As illustrated in  FIG.  15   , the key point extraction apparatus  2   d  in the fourth example embodiment is different from the key point extraction apparatus  2   b  in the second example embodiment in that a feature amount extraction unit  218  and an iris authentication unit  219  are implemented in the arithmetic apparatus  21 . Another feature of the key point extraction apparatus  2   d  may be same as another feature of the key point extraction apparatus  2   b.    
     Note that a detail of an operation of each of the feature amount extraction unit  218  and the iris authentication unit  219  will be described later in detail, however, a summary thereof will be described briefly here. The feature amount extraction unit  218  extracts a feature amount of the iris based on the key point KP of the iris. The iris authentication unit  219  authenticates the person included in the person image IMG 1  based on the feature amount of the iris extracted by the feature amount extraction unit  218 . 
     In this manner, the key point extraction apparatus  2   d  in the fourth example embodiment is capable of performing the iris authentication based on the extracted key point KP. Thus, the key point extraction apparatus  2   d  in the fourth example embodiment may be referred to as an iris authentication apparatus. The key point extraction operation that is performed by the key point extraction apparatus  2   d  in the fourth example embodiment may be referred to as an iris authentication operation. The key point extraction SYSd in the fourth example embodiment may be referred to as an iris authentication system. 
     (4-2) Flow of Key Point Extraction Operation (Iris Authentication Operation) Performed by Key Point Extraction Apparatus  2   d    
     Next, with reference to  FIG.  16   , a flow of the key point extraction operation that is performed by the key point extraction apparatus  2   d  in the fourth example embodiment (the iris authentication operation that is performed by the iris authentication apparatus in the fourth example embodiment) will be described.  FIG.  16    is a flowchart that illustrates the flow of the key point extraction operation that is performed by the key point extraction apparatus  2   d  in the fourth example embodiment (the iris authentication operation that is performed by the iris authentication apparatus in the fourth example embodiment). 
     As illustrated in  FIG.  16   , the key point extraction apparatus  2   d  firstly performs the key point extraction operation in the second example embodiment (the step S 11  to the step S 23 ). Specifically, the key point extraction apparatus  2   d  obtains the person image IMG 1  from the camera  1  (the step S 11 ). Then, the key point extracting unit  215  extracts the key point KP of the iris that is included in the person image IMG 1  from the person image IMG 1  obtained at the step S 11  (the step S 21 ). Then, the image conversion unit  216  generates the conversion image IMG 3  by performing the image conversion processing that convers the person image IMG 1  based on the key point KP extracted at the step S 21  (the step S 22 ). Then, the key point extracting unit  217  extracts the key point KP of the iris from the conversion image IMG 3  generated at the step S 22  (the step S 23 ). 
     Then, the feature amount extraction unit  218  extracts the feature amount of the iris included in the conversion image IMG 3  based on the key point KP of the iris extracted at the step S 23  and the conversion image IMG 3  (a step S 41 ). Note that the feature amount extraction unit  218  may extract the feature amount by using any method for extracting the feature amount of the iris. For example, the feature amount extraction unit  218  may determine a loop-shaped iris area in which the iris is included in the conversion image IMG 3  based on the key point KP of the iris extracted at the step S 23 . Specifically, the feature amount extraction unit  218  may determine the iris area based on the key point KP 1  from which the inner outline of the iris is determinable and the key point KP 2  from which the outer outline of the iris is determinable. Furthermore, the feature amount extraction unit  218  may delete an area part that overlaps with the eyelid from the loop-shaped iris area based on the key point KP 4  from which the edge of the eyelid is determinable. Then, the feature amount extraction unit  218  may divide the iris area into a plurality of ring-shaped blocks, divide each block into a plurality of sectors, and extract a feature amount of each sector (for example, a feature amount relating to a pattern of the iris included in the plurality of sectors, and a brightness value for example). Incidentally, as can be understandable from the description of the feature amount extraction unit  218 , the present disclosure clearly distinguishes a feature point (namely, the key point KP) from the feature amount of the iris. 
     Then, the iris authentication unit  219  authenticates the person included in the conversion image IMG 3  (namely, the person included in the person image IMG 1 ) based on the feature amount of the iris extracted at the step S 42  (a step S 41 ). Note that the iris authentication unit  219  may authenticate the person by using any method for authenticating the person based on the feature amount of the iris. For example, the iris authentication unit  219  may perform a matching between the feature amount that is extracted (hereinafter, it is referred to as an “extracted feature amount”) and the feature amounts of the irises of various persons stored (in other words, registered) in an iris database (hereinafter, it is referred to as a “registered feature amount”). Specifically, the iris authentication unit  219  may calculate a matching score that indicates a similarly between the registered feature amount and the extracted feature amount. Then, the iris authentication unit  219  may authenticate the person included in the conversion image IMG 3  based on the matching score. For example, when the matching score that indicates the similarly between a certain registered feature amount and the extracted feature amount is smaller than a predetermined threshold value, the iris authentication unit  219  may determine that the person included in the conversion image IMG 3  is not a person corresponding to the registered feature amount. On the other hand, for example, when the matching score that indicates the similarly between a certain registered feature amount and the extracted feature amount is larger than the predetermined threshold value, the iris authentication unit  219  may determine that the person included in the conversion image IMG 3  is the person corresponding to the registered feature amount. 
     (4-3) Technical Effect of Key Point Extraction Apparatus  2   d    
     The key point extraction apparatus  2   d  in the fourth example embodiment is capable of achieving an effect that is same as the effect achievable by the key point extraction apparatus  2   b  in the second example embodiment. Furthermore, the key point extraction apparatus  2   d  is capable of authenticating the person included in the person image IMG 1  based on the iris of the person. 
     (4-4) Modified Example of Key Point Extraction Apparatus  2   d    
     In the above described description, the key point extraction apparatus  2   d  in the fourth example embodiment is different from the key point extraction apparatus  2   b  in the second example embodiment in that the feature amount extraction unit  218  and the iris authentication unit  219  are implemented in the arithmetic apparatus  21 . Namely, in the above described description, the key point extraction apparatus  2   b  in the second example embodiment includes the feature amount extraction unit  218  and the iris authentication unit  219 . However, at least one of the key point extraction apparatus  2  in the first example embodiment and the key point extraction apparatus  2   c  in the third example embodiment the feature amount extraction unit  218  and the iris authentication unit  219 . In this case, the feature amount extraction unit  218  may extract the feature amount of the iris based on the key point KP extracted by the key point extraction unit  214  (namely, the key point KP extracted from the target image IMG 1 _TA). 
     The iris database that is used to authenticate the person includes an iris record in which the feature amount of the iris (the registered feature amount) extracted from the image in which a certain person is included is associated with a person identification information for uniquely identifying the person, for example. Especially, the iris database includes a plurality of iris records that correspond to a plurality of persons, respectively, because the feature amounts of the irises of the plurality of persons are stored in the iris database. In this case, the iris database may include the iris record in which the feature amount of the iris extracted from the image that includes the iris of the certain person in a first aspect is associated with the person identification information and the iris record in which the feature amount of the iris extracted from the image that includes the iris of the same person in a second aspect that is different from the first aspect is associated with the person identification information, for example. For example, as described above, the characteristic of the iris may include the size (for example, the diameter) of the iris. In this case, the iris database may include the iris record in which the feature amount of the iris extracted from the image that includes the iris of the person, which is in a state where the size of the iris is a first size, is associated with the person identification information and the iris record in which the feature amount of the iris extracted from the image that includes the iris of the same person, which is in a state where the size of the iris is a second size that is different from the first size, is associated with the person identification information, for example. Even in this case, the iris authentication unit  219  may calculate the matching score by using the iris database that includes the plurality of iris records that correspond to the same person and that correspond to the different characteristics (for example, the sizes) of the iris. Alternatively, the iris authentication unit  219  may extract, from the iris database, a plurality of iris records that correspond to the characteristic (for example, the size) of the iris that is included in the person image IMG 1  obtained from the camera  1  and may calculate the matching score by using the plurality of extracted iris records. 
     (5) Key Point Extraction System SYS in Fifth Example Embodiment 
     Next, the key point extraction system SYS in a fifth example embodiment will be described. Note that the key point extraction system SYS in the fifth example embodiment is referred to as a “key point extraction system SYSe” in the below described description. 
     The key point extraction system SYSe in the fifth example embodiment is different from the above described key point extraction system SYSd in the fourth example embodiment in that it includes a key point extraction apparatus  2   e  instead of the key point extraction apparatus  2   d.  Another feature of the key point extraction system SYSe may be same as another feature of the key point extraction system SYSd. Thus, in the below describe description, with reference to  FIG.  17   , the key point extraction apparatus  2   e  in the fifth example embodiment will be mainly described.  FIG.  17    is a block diagram that illustrates the configuration of the key point extraction apparatus  2   e  in the fifth example embodiment. 
     As illustrated in  FIG.  17   , the key point extraction apparatus  2   e  in the fifth example embodiment is different from the key point extraction apparatus  2   d  in the fourth example embodiment in that a key point extraction unit  217   e  and a feature amount extraction unit  218   e  are implemented in the arithmetic apparatus  21 . Another feature of the key point extraction apparatus  2   e  may be same as another feature of the key point extraction apparatus  2   d.    
     The key point extraction unit  217   e  extracts the key point KP of the iris included in the person image IMG 1  from the person image IMG 1 . Especially, the key point extraction unit  217   e  may be configured to extract one type of key point KP more accurately than the key point extraction unit  217 . For example, the key point extraction unit  217   e  may be configured to extract the key point KP from which the center of the pupil is determinable and the key point KP from which the diameter of the pupil is determinable more accurately than the key point extraction unit  217 . In this case, the key point extraction unit  217   e  may extract an image part of the person image IMG 1  corresponding to the iris based on the key point KP that is extracted by the key point extraction unit  215  to perform the image conversion processing (the key point KP from which the center of the iris is determinable and the key point KP from which the diameter of the iris is determinable), and may extract one type of key point KP (for example, the key point KP from which the center of the pupil is determinable and the key point KP from which the diameter of the pupil is determinable), which is extractable accurately, from the extracted image part. 
     The feature amount extraction unit  218   e  extracts the feature amount of the iris of the person included in the person image IMG 1  based on the key point KP of the iris extracted by the key point extraction unit  217   e  and the person image IMG 1 . 
     In the fifth example embodiment, the iris authentication unit  219  authenticates the person included in the person image IMG 1  based on the feature amount of the iris extracted by the feature amount extraction unit  218   e  and the feature amount of the iris extracted by the feature amount extraction unit  218 . Specifically, the iris authentication unit  219  may calculate the matching score by using the feature amount of the iris extracted by the feature amount extraction unit  218   e  and the iris database and calculate the matching score by using the feature amount of the iris extracted by the feature amount extraction unit  218  and the iris database. Then, the iris authentication unit  219  may authenticate the person included in the conversion image IMG 3  based on the matching scores. 
     The key point extraction apparatus  2   e  in the fifth example embodiment is capable of achieving an effect that is same as the effect achievable by the key point extraction apparatus  2   d  in the fourth example embodiment. 
     Note that the feature amount extraction unit  218   e  extracts the feature amount of the iris based on the key point KP of the iris extracted by the key point extraction unit  217   e  in the above described description. However, the feature amount extraction unit  218   e  may extract the feature amount of the iris based on the key point KP of the iris extracted by the key point extraction unit  217   e  and the key point KP of the iris extracted by the key point extraction unit  215 . For example, the feature amount extraction unit  218   e  may calculate an average value of the key point KP of the iris extracted by the key point extraction unit  217   e  and the key point KP of the iris extracted by the key point extraction unit  215 , and extract the feature amount of the iris based on the calculated average value of the key points KP. 
     Similarly, the feature amount extraction unit  218  extracts the feature amount of the iris based on the key point KP of the iris extracted by the key point extraction unit  217  in the above described description. However, the feature amount extraction unit  218  may extract the feature amount of the iris based on the key point KP of the iris extracted by the key point extraction unit  217  and the key point KP of the iris extracted by the key point extraction unit  215 . For example, the feature amount extraction unit  218  may calculate an average value of the key point KP of the iris extracted by the key point extraction unit  217  and the key point KP of the iris extracted by the key point extraction unit  215 , and extract the feature amount of the iris based on the calculated average value of the key points KR Incidentally, the key point extraction unit  215  extracts the key point KP from the person image IMG 1  and the key point extraction unit  217  extracts the key point KP from the conversion image IMG 3  (namely, the image that is obtained by performing the image conversion processing on the person image IMG 1 ). Thus, there is a possibility that the position of the key point KP of a certain part (for example, the center of the iris) extracted by the key point extraction unit  217  is different from the position of the key point KP of the same part extracted by the key point extraction unit  215  by an amount based on the image conversion processing. Thus, the feature amount extraction unit  218  may perform the coordinate transformation, which is based on the image conversion processing, on the key point KP extracted by at least one of the key point extraction units  215  and  217 . Then, the feature amount extraction unit  218  may extract the feature amount of the iris based on the key point KP on which the coordinate transformation is performed. 
     (6) Supplementary Note 
     With respect to the example embodiments described above, the following Supplementary Notes will be further disclosed. 
     [Supplementary Note 1] 
     An information processing apparatus comprising: 
     a reducing unit that generates a second image by reducing a first image in which a target object is included; 
     a first extracting unit that extracts, as a first key point, a key point of the target object from the second image; 
     a setting unit that sets a target area that designates a part of the first image based on the first key point; and 
     a second extracting unit that extracts, as a second key point, a key point of the target object from a target image of the first image that is included in the target area. 
     [Supplementary Note 2] 
     The information processing apparatus according to Supplementary Note 1, wherein 
     the setting unit is configured to change a size of the target area. 
     [Supplementary Note 3] 
     The information processing apparatus according to Supplementary Note 2, wherein 
     the setting unit is configured to change the size of the target area based on the first key point. 
     [Supplementary Note 4] 
     The information processing apparatus according to Supplementary Note 2 or 3, wherein 
     the target object includes an iris of a living body, 
     the setting unit is configured to change the size of the target area to be a size based on a size of the iris indicated by the first key point. 
     [Supplementary Note 5] 
     The information processing apparatus according to any one of Supplementary Notes 1 to 4 further comprising: 
     a third extracting unit that extracts, as a third key point, a key point of the target object from a third image in which the target object is included; and 
     an image converting unit that generates the first image by performing an image conversion processing that converts the third image based on the third key point. 
     [Supplementary Note 6] 
     The information processing apparatus according to Supplementary Note 5, wherein 
     the target object includes an iris of a living body, 
     the image conversion processing includes a translation processing that translates the third image so that a center of the iris is closer to a center of the third image. 
     [Supplementary Note 7] 
     The information processing apparatus according to Supplementary Note 5 or 6, wherein 
     the target object includes an outer corner of an eye and an inner corner of the eye of a living body, 
     the image conversion processing includes a rotation processing that rotates the third image so that a line that connects the outer corner of the eye and the inner corner of the eye is closer to be horizontal in the third image. 
     [Supplementary Note 8] 
     The information processing apparatus according to any one of Supplementary Notes 5 to 7, wherein 
     the target object includes an iris of a living body, 
     the image conversion processing includes a scaling processing that scales the third image so that a size of the iris in the third image is closer to a predetermined size. 
     [Supplementary Note 9] 
     The information processing apparatus according to any one of Supplementary Notes 5 to 8, wherein 
     the image conversion processing includes a brightness conversion processing that normalizes a brightness of the third image. 
     [Supplementary Note 10] 
     An information processing method comprising: 
     generating a second image by reducing a first image in which a target object is included; 
     extracting, as a first key point, a key point of the target object from the second image; 
     setting a target area that designates a part of the first image based on the first key point; and 
     extracting, as a second key point, a key point of the target object from a target image of the first image that is included in the target area. 
     [Supplementary Note 11] 
     A recording medium on which a computer program that allows a computer to execute an information processing method is recorded, 
     the information processing method comprising: 
     generating a second image by reducing a first image in which a target object is included; 
     extracting, as a first key point, a key point of the target object from the second image; 
     setting a target area that designates a part of the first image based on the first key point; and 
     extracting, as a second key point, a key point of the target object from a target image of the first image that is included in the target area. 
     At least a part of the feature of each embodiment described above may be combined with at least other part of the feature of each embodiment described above. A part of the feature of each embodiment described above may not be used. Moreover, the disclosures of all documents (for example, publications) that are cited in the present disclosure described above are incorporated in the present disclosure by reference if it is legally permitted. 
     The present disclosure is allowed to be changed, if desired, without departing from the essence or spirit of the invention which can be read from the claims and the entire specification, and an information processing apparatus, an information processing method, a computer program and a recording medium, which involve such changes, are also intended to be within the technical scope of the present disclosure. 
     DESCRIPTION OF REFERENCE CODES 
       1  camera 
       2  key point extraction apparatus 
       21  arithmetic apparatus 
       211  image reduction unit 
       212  key point extraction unit 
       213  target area set unit 
       214  key point extraction unit 
       215  key point extraction unit 
       216  image conversion unit 
       217  key point extraction unit 
       218  feature amount extraction unit 
       219  iris authentication unit 
       3  communication network 
     SYS key point extraction system 
     IMG 1  person image 
     IMG 2  reduction image 
     IMG 3  conversion image 
     IMG 1 _TA target image 
     TA target area 
     KP key point