Patent Publication Number: US-2022237951-A1

Title: Spoofing detection apparatus, spoofing detection method, and computer-readable recording medium

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     The present application is a continuation application of U.S. patent application Ser. No. 16/964,877 filed on Jul. 24, 2020, which is a National Stage Entry of PCT/JP2018/006561 filed on Feb. 22, 2018, the contents of all of which are incorporated herein by reference, in their entirety. 
    
    
     TECHNICAL FIELD 
     The present invention relates to a spoofing detection apparatus and a spoofing detection method for performing spoofing detection during face authentication, and also to a computer-readable recording medium, in which a program for realizing the apparatus and method is recorded. 
     BACKGROUND ART 
     Log-in systems that use a biometric authentication technique such as face authentication have the advantage of being unburdened by storing and managing a password, unlike log-in systems that use a password. 
     However, in a log-in system that uses a biometric authentication technique, even if an authorized person properly uses the system, there is the possibility that an authentication error will occur, unlike log-in systems that use a password. Furthermore, in a log-in system that uses a biometric authentication technique, there is the possibility that a third party will be recognized as an authorized person by mistake, and there is the possibility that, when a malicious third party attempts authentication using an image or a moving image of the authorized person, the image will be authenticated. 
     Therefore, in log-in systems that use a biometric authentication technique, from the viewpoint of security, such impersonated (spoofing) log-in by a third party that is not an authorized person has been a serious problem, and there has been increasing demand for detection techniques for preventing spoofing. 
     Particularly, if face authentication is used in login for an application program on a mobile terminal, it is generally more difficult to take measures against spoofing since types of hardware that are mounted in a mobile terminal are limited. Examples of a technique that is used in a spoofing detection system for face authentication include a technique that uses a special sensor such as an infrared camera, a technique for performing shooting in different directions using a plurality of cameras, and a technique for measuring the depth of a face using focus switching. 
     However, currently, mobile terminals are not usually equipped with hardware required for using these techniques. Examples of types of hardware mounted in a large number of mobile terminals, from among types of hardware that can be used for spoofing detection during face authentication, include an sub-camera directed to the user side and a light-emitting apparatus (flash) provided in association with the sub-camera. Therefore, techniques for performing spoofing detection using these have been proposed (for example, see Patent Document 1). 
     Specifically, Patent Document 1 discloses a spoofing detection apparatus that uses the fact that, in a case of a real human&#39;s face, light of the flash of a camera is specularly reflected in the iris region of an eye, and, as a result, appears as a bright point in an image, but the same phenomenon does not occur in a face in a photograph or an image on a display. 
     The spoofing detection apparatus disclosed in Patent Document 1 first compares an image shot when the flash was on with an image shot when the flash was off, and extracts a bright point portion in the former image. Next, the spoofing detection apparatus performs spoofing detection by obtaining a feature of the extracted portion, and comparing the obtained feature with a feature obtained from a reference image shot in advance. 
     LIST OF PRIOR ART DOCUMENTS 
     Patent Document 
     
         
         Patent Document 1: Japanese Patent No. 4609253 
       
    
     SUMMARY OF INVENTION 
     Problems to be Solved by the Invention 
     Incidentally, a bright point formed by specular reflection in an iris region of an eye is position-dependent, and the bright point changes depending on the shooting conditions of an image. In other words, in general, a position at which a bright point appears changes depending on conditions such as the positions of a light-emitting apparatus, an eyeball, and a camera in a space. As a result, the feature of the bright point portion also changes depending on the positional relation between the mobile terminal and the face during shooting, and the accuracy of spoofing detection decreases. 
     Therefore, the spoofing detection apparatus disclosed in Patent Document 1 estimates a position on an eyeball at which specular reflection of light from a flash will occur, and corrects the feature of a bright point portion using the estimation result, in order to dissolve the dependence on the position of the bright point. 
     Specifically, the spoofing detection apparatus first specifies an iris portion of an eye, and estimates a gaze direction of the eye based on the ellipsoidal shape of the specified iris portion. Next, the spoofing detection apparatus estimates a position at which a bright point will occur due to a flash, based on positional information of the camera obtained in advance and the estimated gaze direction, and corrects the feature of the bright point portion based on the estimation result. 
     However, in actuality, it is difficult to correct a feature when the position of a bright point has shifted, to be the same as a feature when the position of the bright point has not shifted, due to the properties of a feature. Therefore, in the spoofing detection apparatus disclosed in Patent Document 1, when the feature of a bright point portion changes due to the positional relation between the mobile terminal and the face during shooting, it is difficult to suppress a decrease in the accuracy of spoofing detection. 
     An example object of the invention is to provide a spoofing detection apparatus, a spoofing detection method, and a computer-readable recording medium that dissolve the above issue, and enable execution of spoofing detection without being affected by dependence on the position of a reflection bright point during face authentication. 
     Means for Solving the Problems 
     In order to achieve the above-described example object, a spoofing detection apparatus according to an example aspect of the invention includes:
         a memory storing a program; and   a processor configured to run the program to execute:   obtaining, from an image capture apparatus, a first image frame that includes a face of a subject person when light was emitted from a light-emitting apparatus associated with the image capture apparatus and a second image frame that includes the face of the subject person when the light-emitting apparatus was turned off;   extracting information specifying a face portion of the subject person as first face information, from the first image frame, and extract information specifying a face portion of the subject person as second face information, from the second image frame;   extracting a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, from the first image frame, based on the first face information, also extract a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information, and calculate, based on the two extracted portions, a feature that is independent of a position of the bright point; and   determining authenticity of the subject person captured by the image capture apparatus, based on the feature.       

     In addition, in order to achieve the above-described example object, a spoofing detection method according to an example aspect of the invention includes:
         obtaining, from an image capture apparatus, a first image frame that includes a face of a subject person when light was emitted from a light-emitting apparatus associated with the image capture apparatus and a second image frame that includes the face of the subject person when the light-emitting apparatus was turned off;   extracting information specifying a face portion of the subject person as first face information, from the first image frame, and extracting information specifying a face portion of the subject person as second face information, from the second image frame;   extracting a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, from the first image frame, based on the first face information, also extracting a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information, and calculating, based on the two extracted portions, a feature that is independent of a position of the bright point; and   determining authenticity of the subject person captured by the image capture apparatus, based on the feature.       

     Furthermore, in order to achieve the above-described example object, a non-transitory computer-readable recording medium according to an example aspect of the invention that includes a program recorded thereon, the program including instructions that cause a computer to carry out:
         obtaining, from an image capture apparatus, a first image frame that includes a face of a subject person when light was emitted from a light-emitting apparatus associated with the image capture apparatus and a second image frame that includes the face of the subject person when the light-emitting apparatus was turned off;   extracting information specifying a face portion of the subject person as first face information, from the first image frame, and extracting information specifying a face portion of the subject person as second face information, from the second image frame;   extracting a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, from the first image frame, based on the first face information, also extracting a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information, and calculating, based on the two extracted portions, a feature that is independent of a position of the bright point; and   determining authenticity of the subject person captured by the image capture apparatus, based on the feature.       

     Advantageous Effects of the Invention 
     As described above, according to the invention, during face authentication, spoofing detection can be executed without being affected by dependence on the position of a reflection bright point. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is an explanatory diagram showing an example of a technique for extracting a bright point formed by light reflection in the iris region of an eye according to the invention. 
         FIG. 2  is an explanatory diagram showing a feature calculated according to the invention and a feature calculated according to a conventional technique, in comparison. 
         FIG. 3  is a block diagram showing the configuration of a spoofing detection apparatus according to a first example embodiment of the invention. 
         FIG. 4  is a diagram showing an example of features obtained according to the first example embodiment of the invention. 
         FIG. 5  is a flowchart showing operations of the spoofing detection apparatus according to the first example embodiment of the invention. 
         FIG. 6  is a block diagram showing the configuration of a spoofing detection apparatus according to a second example embodiment of the invention. 
         FIG. 7  is a flowchart showing operations of the spoofing detection apparatus according to the second example embodiment of the invention. 
         FIG. 8  is a flowchart showing operations of a spoofing detection apparatus according to a third example embodiment of the invention. 
         FIG. 9  is a diagram showing an example of a feature calculated based on an iris region and a feature calculated based on a face region according to the third example embodiment. 
         FIG. 10  is a block diagram showing an example of a computer that realizes the spoofing detection apparatuses according to the first to third example embodiments of the invention. 
     
    
    
     MODE FOR CARRYING OUT THE INVENTION 
     Summary of Invention 
     First, before describing example embodiments of the invention, summary of the invention will be described. As described above, the position of a bright point formed by reflection in an iris region of an eye changes depending on an angle at which light from a flash is incident to the iris region and orientation of the face of the subject person. Therefore, in Patent Document 1 described in BACKGROUND ART, the position of a bright point is estimated, and spoofing detection is performed based on the estimated position of the bright point. In contrast, in the invention, as will be described later, a feature for which the positional dependence is dissolved is used. 
     Here, a method for calculating a feature for which the positional dependence is dissolved, based on an image shot when a flash was on and an image shot when the flash was off, according to the invention will be described in comparison to a conventional method for calculating a feature, with reference to  FIGS. 1 and 2 .  FIG. 1  is an explanatory diagram showing an example of a technique for extracting a bright point formed by reflection on an iris region of an eye, according to the invention.  FIG. 2  is an explanatory diagram showing a feature calculated according to the invention and a feature calculated according to a conventional technique, in comparison. 
     First, as shown on the upper side of  FIG. 1 , a user  101  shoots their own face at least once using a terminal apparatus  102  equipped with a camera when the flash is on, and also shoots their own face at least once using a terminal apparatus  103  equipped with a camera when the flash is off. In the invention, a bright point portion is extracted from images obtained through such shooting, and a feature of the extracted bright point portion is calculated. 
       FIG. 1  shows an image  105  that represents an image when the flash is on, and an image  106  that represents an image when the flash is off. According to the invention, a bright point portion is extracted by comparing both the images, and a feature is calculated for the extracted portion. In addition, according to the invention, if a bright point portion can be extracted, it is determined that the face that appears in the images  105  and  106  is a real human face. On the other hand, if no bright point portion can be extracted, it is determined that the face that appears in the images  105  and  106  is a fake face. 
     However, as described above, the position of a bright point formed by flash reflection changes depending on shooting conditions. Therefore, as shown in images  201  and  202  on the left side of  FIG. 2 , there is the possibility that, even in the same real face, the position of a bright point will deviate. If the position of a bright point deviates, when images are converted into a feature of a one-dimensional vector, a different feature will be calculated. 
     A feature  203  shown in the center of  FIG. 2  is calculated based on the image  201 , and a feature  204  is calculated based on the image  202 . The feature  203  and the feature  204  are calculated based on bright points that differ only in their positions, but the similarity between these amounts is low. In addition, this decrease in similarity leads to a decrease in the determination accuracy. Note that both the feature  203  and the feature  204  are features based on which a determination as a real face should be made. As described above, the spoofing detection apparatus disclosed in Patent Document 1 copes with this problem by estimating the position of a bright point, and correcting a feature based on the estimation result. 
     In contrast, according to the invention, in place of estimation of the position of a bright point that involves a certain degree of uncertainty, a feature  205  and a feature  206  shown on the right side of  FIG. 2  are calculated. The feature  205  and the feature  206  are features that are independent of the position of a bright point. Therefore, according to the invention, it is possible to more easily and more accurately perform spoofing detection that is robust against an environment change. 
     Example embodiments of the invention will be described below. Note that the following description and drawings are omitted and simplified as appropriate for clarification. In addition, in the drawings, the same reference signs are assigned to the same constituent elements, and redundant description is omitted as necessary. In addition, specific numerical values and the like mentioned in the example embodiments are merely exemplary for ease of understanding of the invention, and there is no limitation thereto. 
     First Example Embodiment 
     A spoofing detection apparatus, a spoofing detection method, and a program according to a first example embodiment of the invention will be described below with reference to  FIGS. 3 to 5  below. 
     [Apparatus Configuration] 
     First, the configuration of the spoofing detection apparatus according to the first example embodiment will be described with reference to  FIG. 3 .  FIG. 3  is a block diagram showing the configuration of the spoofing detection apparatus according to the first example embodiment of the invention. 
     A spoofing detection apparatus  300  according to the first example embodiment shown in  FIG. 3  is an apparatus for performing spoofing detection during face authentication. As shown in  FIG. 1 , the spoofing detection apparatus  300  includes a face image obtaining unit  301 , a face information extraction unit  302 , a feature calculation unit  303 , and a spoofing determination unit  304 . 
     The face image obtaining unit  301  obtains, from an image capture apparatus  310 , a first image frame that includes the face of a subject person when light was emitted by a light-emitting apparatus  320  accompanying the image capture apparatus  310  and a second image frame that includes the face of the subject person when the light-emitting apparatus  320  was turned off. 
     The face information extraction unit  302  extracts, from the first image frame, information specifying a face portion of the subject person as first face information. The face information extraction unit  302  also extracts, from the second image frame, information specifying a face portion of the subject person as second face information. 
     The feature calculation unit  303  extracts, from the first image frame, a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, based on the first face information. The feature calculation unit  303  also extracts, from the second image frame, a portion corresponding to the above portion that includes the bright point, based on the second face information. The feature calculation unit  303  then calculates, based on the two extracted portions, a feature that is independent of the position of the bright point. 
     The spoofing determination unit  304  determines authenticity of the subject person captured by the image capture apparatus  310 , based on the feature calculated by the feature calculation unit  303 . Specifically, the spoofing determination unit  304  determines whether or not the captured subject person is a real human. 
     As described above, in the first example embodiment, the spoofing detection apparatus  300  can calculate a feature that is independent of the position of a bright point, unlike the conventional spoofing detection apparatus described in BACKGROUND ART (see  FIG. 2  above). Therefore, according to the first example embodiment, during face authentication, it is possible to perform spoofing detection without being affected by dependence on the position of a reflection bright point. 
     Subsequently, the configuration of the spoofing detection apparatus  300  according to the first example embodiment will be described in more detail. First, as shown in  FIG. 1 , according to the first example embodiment, the spoofing detection apparatus  300  is connected to the image capture apparatus  310  that includes the light-emitting apparatus  320 . Examples of the image capture apparatus  310  include a digital camera and a digital video camera. 
     As described above, the face image obtaining unit  301  obtains a first image frame shot when the light-emitting apparatus was emitting light and a second image frame shot when the light-emitting apparatus was turned off. In addition, the first image frame and the second image frame that are obtained at this time may be image frames of still images, or may also be image frames of moving images. 
     According to the first example embodiment, the face information extraction unit  302  first detects the region of a face portion of a subject person (hereinafter, referred to as “face region”), from each of the first image frame and the second image frame. Specifically, the face information extraction unit  302  detects a face region, for example, using a Haar-like feature. A method for detecting a face region using a Haar-like feature is disclosed in Reference Document 1 below, for example. 
     Reference Document 1 
     
         
         P. Viola and M. Jones, “Rapid Object Detection Using a Boosted Cascade of Simple Features,” Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), Vol. 1, 2001, pp. 511-518. 
       
    
     Next, the face information extraction unit  302  extracts first face information from the face region extracted from the first image frame, and extracts second face information from the face region extracted from the second image frame. Specifically, the face information extraction unit  302  estimates the regions of the parts of the face based on the face region, and defines information specifying the positions of the estimated regions of the parts as face information. In addition, the face information includes information specifying the position of an estimated iris region. 
     In addition, as examples of a method for estimating an iris region include a method for first detecting eye regions, calculating the distance between the eyes, next, using this distance between the eyes to set a square whose center is the same as the center of each of the eyes, and each side of which is one sixth of the distance between the eyes, and defining the region of this square as an iris region. In addition, examples of a method for detecting an eye region include a method that uses a ring Gabor filter, which is disclosed in Reference Document 2 below. 
     Reference Document 2 
     
         
         Zhang, Y., Sun, N., Gao, Y., and Cao, M. (2008). A new eye location method based on Ring Gabor Filter. In Automation and Logistics, 2008. ICAL2008. IEEE International Conference On, (IEEE), pp. 301-305. 
       
    
     In the first example embodiment, the feature calculation unit  303  extracts an iris region in the first image frame (hereinafter, referred to as a “first iris region”), using the first face information, and also extracts an iris region in the second image frame (hereinafter, referred to as a “second iris region”), using the second face information. 
     The feature calculation unit  303  then obtains a luminance value L in  of each pixel of the first iris region and a luminance value L out  of each pixel of the second iris region, and calculates the difference between these values (Lin−Lout) as a temporary feature, for each pixel. In addition, the feature calculation unit  303  can also perform standardization, scaling, or the like on the temporary feature (L in −L out ), and transform this into a manageable form. 
     Subsequently, the feature calculation unit  303  executes conversion processing for dissolving the positional dependence, on the temporary feature in order to obtain a feature that is independent of the position of the bright point. For example, the feature calculation unit  303  performs the conversion by converting the temporary feature (difference (L in −L out ) for each pixel) calculated based on the iris regions, which are two-dimensional planes, into a one-dimensional vector, and sorting the values of the respective pixels in ascending order or descending order. The feature that underwent conversion in this manner is a feature for which the positional dependence is dissolved. 
       FIG. 4  is a diagram showing an example of a feature obtained according to the first example embodiment of the invention. In the example in  FIG. 4 , a feature  601  is a feature obtained when the subject person is a real human. A feature  602  is a feature obtained from a face in a photograph or an image. 
     According to the first example embodiment, the spoofing determination unit  304  determines the authenticity of a subject person, that is to say whether or not the subject person is a real human, by applying a feature calculated by the feature calculation unit  303  to a classifier created in advance. 
     Specifically, examples of the classifier include an SVM binary classifier constructed using an SVM (Support Vector Machine). In addition, this classifier is constructed by preparing a feature calculated in advance based on an image of a real human face and a feature calculated based on an image of a fake human face, and performing learning using these features. Note that a method for constructing a classifier using a Support Vector Machine is disclosed in Reference Document 3 below. 
     Reference Document 3 
     
         
         V. Vapnik and A. Lerner. Pattern recognition using generalized portrait method. Automation and Remote Control, 24, 1963. 
       
    
     [Apparatus Operations] 
     Next, operations of the spoofing detection apparatus  300  according to the first example embodiment of the invention will be described with reference to  FIG. 5 .  FIG. 5  is a flowchart showing operations of the spoofing detection apparatus according to the first example embodiment of the invention. In the following description,  FIGS. 3 and 4  will be referred to as appropriate. In addition, according to the first example embodiment, the spoofing detection method is carried out as a result of causing the spoofing detection apparatus  300  to operate. Thus, a description of the spoofing detection method according to the first example embodiment is replaced with the following description of operations of the spoofing detection apparatus  300 . 
     As shown in  FIG. 5 , first, the face image obtaining unit  301  obtains, from the image capture apparatus  310 , a first image frame that includes the face of a subject person when light was emitted from the light-emitting apparatus  320  associated with the image capture apparatus  310  and a second image frame that includes the face of the subject person when the light-emitting apparatus  320  was turned off (step A 1 ). 
     Next, the face information extraction unit  302  extracts, from the first image frame, information specifying a face portion of the subject person as first face information, and also extracts, from the second image frame, information specifying a face portion of the subject person as second face information (step A 2 ). 
     Next, the feature calculation unit  303  extracts a portion that includes a bright point, from the first image frame based on the first face information, and extract a portion corresponding to the portion that includes the bright point, from the second image frame based on the second face information. The feature calculation unit  303  then calculates a feature that is independent of the position of the bright point, based on the two extracted portions (step A 3 ). 
     Specifically, in step A 3 , the feature calculation unit  303  first extracts a first iris region in the first image frame using the first face information, and also extracts a second iris region in the second image frame using the second face information. Next, the feature calculation unit  303  calculates a difference between the luminance value L in  of each pixel of the first iris region and the luminance value L out  of each pixel of the second iris region (L in −L out ), as a temporary feature, for each pixel. The feature calculation unit  303  then executes conversion processing for dissolving the positional dependence, on the temporary feature, and calculates a feature for which the positional dependence is dissolved. 
     The spoofing determination unit  304  then determines the authenticity of the subject person captured by the image capture apparatus  310 , based on the feature calculated by the feature calculation unit  303  in step A 3  (step A 4 ). Specifically, the spoofing determination unit  304  determine whether or not the captured subject person is a real human. 
     After executing step A 4 , the spoofing detection apparatus notifies the determination result to an apparatus that uses a detection result. If the detection result indicates a real human, the apparatus that has received the notification continues authentication processing, and, if the detection result does not indicate a real human, the apparatus stops authentication processing. 
     Effect of First Example Embodiment 
     As described above, according to the first example embodiment, the spoofing detection apparatus  300  calculates a feature that is independent of the position of a bright point formed in an iris region of an eye of a subject person, and can perform determination of whether or not spoofing has occurred, based on this feature. Therefore, according to the first example embodiment, spoofing detection can be performed without being affected by the positional relation between the image capture apparatus  310  and a face, in other words, without being affected by dependence on the position of a reflection bright point. 
     [Program] 
     The program according to the first example embodiment may be a program for causing a computer to execute steps A 1  to A 4  shown in  FIG. 5 . The spoofing detection apparatus  300  and the spoofing detection method according to the first example embodiment can be realized as a result of installing this program to a computer, and executing this program. In this case, the processor of the computer functions as the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , and the spoofing determination unit  304 , and performs processing. 
     In addition, the program according to the first example embodiment may also be executed by a computer system constituted by a plurality of computers. In this case, for example, each of the computers may also function as one of the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , and the spoofing determination unit  304 . 
     Second Example Embodiment 
     Next, a spoofing detection apparatus, a spoofing detection method, and a program according to a second example embodiment of the invention will be described with reference to  FIGS. 6 and 7 . 
     [Apparatus Configuration] 
     First, the configuration of the spoofing detection apparatus according to the second example embodiment will be described with reference to  FIG. 6 .  FIG. 6  is a block diagram showing the configuration of the spoofing detection apparatus according to the second example embodiment of the invention. 
     As shown in  FIG. 6 , a spoofing detection apparatus  350  according to the second example embodiment is constituted by a mobile terminal apparatus  500 . Specifically, the spoofing detection apparatus  350  is constituted by a program that operates on the operating system of the terminal apparatus  500 . In addition, the terminal apparatus  500  includes the image capture apparatus  310 , the light-emitting apparatus  320 , a display device  330 , and an input device  340 . 
     As shown in  FIG. 6 , also according to the second example embodiment, the spoofing detection apparatus  350  includes the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , and the spoofing determination unit  304 , similarly to the spoofing detection apparatus  300  according to the first example embodiment shown in  FIG. 3 . Functions of these are the same as those described in the first example embodiment. 
     Note that, according to the second example embodiment, the spoofing detection apparatus  350  further includes a shooting control unit  305 , unlike the first example embodiment. The shooting control unit  305  controls shooting that is performed by the image capture apparatus  310  and on/off of the light-emitting apparatus  320 , and sets a light-emitting period of the light-emitting apparatus  320  and a shooting timing of the image capture apparatus  310 . 
     Specifically, the shooting control unit  305  instructs the light-emitting apparatus  320  to emit light, and then instruct the image capture apparatus  310  to perform shooting for 150 milliseconds. Thereafter, the shooting control unit  305  instructs the light-emitting apparatus  320  to turn off, and then instructs the image capture apparatus  310  to perform shooting for 150 milliseconds. 
     [Apparatus Operations] 
     Next, operations of the spoofing detection apparatus  350  according to the second example embodiment of the invention will be described with reference to  FIG. 7 .  FIG. 7  is a flowchart showing operations of the spoofing detection apparatus according to the second example embodiment of the invention. In the following description,  FIG. 6  will be referred to as appropriate. In addition, according to the second example embodiment, the spoofing detection method is carried out as a result of causing the spoofing detection apparatus  350  to operate. Thus, a description of the spoofing detection method according to the second example embodiment is replaced with the following description of operations of the spoofing detection apparatus  350 . 
     Note that, in the example in  FIG. 7 , an image of the face of a subject person when light is emitted and an image when light is not emitted are shot. In addition, a light-emitting period of the light-emitting apparatus  320  is 300 milliseconds, and one image is shot in 150 milliseconds after light emission is started, and another image is shot in 150 milliseconds after the light was turned off. 
     As shown in  FIG. 7 , first, when the terminal apparatus  500  is instructed to perform authentication, the shooting control unit  305  instructs the light-emitting apparatus  320  to emit light at the same time as shooting (step B 1 ), and also instructs the image capture apparatus  310  to perform shooting (step B 2 ). 
     When step B 2  is executed, shooting is performed by the image capture apparatus  310 , and image data is output, and thus the face image obtaining unit  301  obtains the output image data as a first image frame (step B 3 ). 
     Next, after step B 3  is executed, the shooting control unit  305  instructs the light-emitting apparatus  320  to turn off (step B 4 ), and further instructs the image capture apparatus  310  to perform shooting (step B 5 ). 
     When step B 5  is executed, shooting is performed by the image capture apparatus  310 , and image data is output, and thus the face image obtaining unit  301  obtains the output image data as a second image frame (step B 6 ). 
     Next, the face information extraction unit  302  extracts information specifying a face portion of the subject person as first face information, from the first image frame obtained in step B 3 , and also extracts information specifying a face portion of the subject person as second face information, from the second image frame obtained in step B 6  (step B 7 ). 
     Next, the feature calculation unit  303  extracts a portion that includes a bright point, from the first image frame based on the first face information, and extracts a portion corresponding to the portion that includes the bright point, from the second image frame based on the second face information. The feature calculation unit  303  then calculates, based on the two extracted portions, a feature that is independent of the position of the bright point (step B 8 ). 
     Next, the spoofing determination unit  304  determines the authenticity of the subject person captured by the image capture apparatus  310 , based on the feature calculated by the feature calculation unit  303  in step B 8  (step B 9 ). Specifically, the spoofing determination unit  304  determine whether or not the captured subject person is a real human. Note that steps B 7  to B 9  are similar to the corresponding steps A 2  to A 4  shown in  FIG. 5 . 
     Thereafter, the spoofing determination unit  304  presents the result of the determination performed in step B 9  (detection result), on a screen using the display device  330  of the terminal apparatus  500  (step B 10 ). Accordingly, the user of the terminal apparatus  500  can confirm the detection result. In addition, if the detection result indicates a real human, the terminal apparatus  500  continues authentication processing, and if the detection result does not indicate a real human, the terminal apparatus  500  stops authentication processing. 
     Effect of Second Example Embodiment 
     As described above, also in the second example embodiment, similarly to the first example embodiment, the spoofing detection apparatus  350  can calculate a feature that is independent of the position of a bright point formed in the iris region of an eyes of a subject person, and determine whether or not spoofing has occurred, based on this feature. Therefore, according to the second example embodiment, spoofing detection can be performed without being affected by the positional relation between the image capture apparatus  310  and the face, in other words, without being affected by dependence on the position of a reflection bright point. 
     [Program] 
     The program according to the second example embodiment may be a program for causing a computer to execute steps B 1  to B 10  shown in  FIG. 7 . The spoofing detection apparatus  350  and the spoofing detection method according to the second example embodiment can be realized as a result of installing this program to a computer, and executing this program. In this case, the processor of the computer functions as the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , the spoofing determination unit  304 , and the shooting control unit  305 , and performs processing. 
     In addition, the program according to the second example embodiment may also be executed by a computer system constituted by a plurality of computers. In this case, for example, each of the computers may also function as one of the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , the spoofing determination unit  304 , and the shooting control unit  305 . 
     Third Example Embodiment 
     Next, a spoofing detection apparatus, a spoofing detection method, and a program according to a third example embodiment of the invention will be described with reference to  FIGS. 8 and 9 . 
     [Apparatus Configuration] 
     First, the configuration of the spoofing detection apparatus according to the third example embodiment will be described. In this third example embodiment, the configuration of the spoofing detection apparatus is similar to the configuration of the spoofing detection apparatus  350  according to the second example embodiment shown in  FIG. 6 . Therefore, in the third example embodiment,  FIG. 6  will be referred to. 
     However, the spoofing detection apparatus according to the third example embodiment is different from the spoofing detection apparatus  350  according to the second example embodiment, in the functions of the feature calculation unit  303  and the spoofing determination unit  304 . The differences will be mainly described below. 
     According to the third example embodiment, more accurate spoofing detection is achieved. Therefore, the feature calculation unit  303  calculates a second feature, in addition to a feature independent of the position of a bright point (hereinafter, referred to as a “first feature”) described in the first and second example embodiments, and integrates these features. 
     According to the third example embodiment, the second feature is a feature that is obtained based on diffuse reflection on the face of a subject person, and that reflects the three-dimensional shape of the face. Specular reflection that occurs in an iris region does not occur in the face region of a human, and the light of a flash is diffusely reflected due to the three-dimensional (uneven) shape of the face. Therefore, if a feature that reflects the three-dimensional shape of the face is calculated based on the pattern of this diffuse reflection, it is possible to perform determination between a real three-dimensional face and a face in a two-dimensional photograph or a face on a display screen. 
     Specifically, the feature calculation unit  303  specifies a face region of the subject person (hereinafter, referred to as a “first face region”), from the first image data, based on the first face information, and also specifies a face region of the subject person (hereinafter, referred to as a “second face region”), from the second image data, based on the second face information. The feature calculation unit  303  then obtains the difference between the luminance distribution of the first face region and the luminance distribution of the second face region, and calculates a second feature based on the obtained difference. 
     Here, a method for calculating a second feature will be described. First, Lambert&#39;s model, which is a model of diffuse reflection, is examined. In Lambert&#39;s model, an observed luminance value L is considered as deriving from a light source component I, a reflection coefficient K, and an angular component θ of a surface as follows. 
         L (λ)= IK (λ)cos θ  (1)
 
     Here, since K is a function of a light wavelength λ, the observed luminance value L is also a function of the light wavelength λ. Thus, it can be said that the luminance value L is an observed value that is dependent on the light wavelength λ, in other words, the color of light. However, if a feature changes depending on the color of the surface of a face, spoofing detection cannot be accurately performed. In view of this, a second feature that is independent of the reflection coefficient K is calculated using an image when the light-emitting apparatus  320  is emitting light and an image when the light-emitting apparatus  320  is turned off. Specifically, the second feature is calculated as follows. 
     The luminance value L in  of each pixel of the first image frame shot when the light-emitting apparatus  320  was emitting light and the luminance value L out  of each pixel of the second image frame shot when the light-emitting apparatus  32  was turned off can be respectively expressed as Expressions 2 and 3 below. 
         L   in (λ, x,y )= I   c   K (λ, x,y )cos θ c   +I   b   K (λ, x,y )cos θ b   (2)
 
         L   out (λ, x,y )= I   b   K (λ, x,y )cos θ b   (3)
 
     Here, similar to Expression 1 above, I is a light source component, K is a reflection coefficient that is dependent on a color, and θ is an angular component of a surface. In addition, Ic and Ib respectively indicate the intensity of light of the flash of a camera and the intensity of background light (ambient light). x and y indicate a position of a pixel in an image frame. θc and θb respectively indicate an incident angle of camera light and an incident angle of background light. Obtaining a second feature that is independent of the color of the surface of a face region, and that reflects the three-dimensional shape of the face is the same as obtaining a feature that is independent of K. In view of this, Expression 4 below is introduced as a feature for which the ratio of the luminance value L in  to the luminance value L out  for each pixel is used. 
     
       
         
           
             
               
                 
                   
                     
                       
                         
                           
                             
                               L 
                               in 
                             
                             - 
                             
                               L 
                               out 
                             
                           
                           
                             
                               L 
                               in 
                             
                             + 
                             
                               L 
                               out 
                             
                           
                         
                         = 
                           
                         
                           
                             
                               I 
                               c 
                             
                             ⁢ 
                             
                               K 
                               ⁡ 
                               ( 
                               
                                 λ 
                                 , 
                                 x 
                                 , 
                                 y 
                               
                               ) 
                             
                             ⁢ 
                             cos 
                             ⁢ 
                             
                               θ 
                               c 
                             
                           
                           
                             
                               
                                 I 
                                 c 
                               
                               ⁢ 
                               
                                 K 
                                 ⁡ 
                                 ( 
                                 
                                   λ 
                                   , 
                                   x 
                                   , 
                                   y 
                                 
                                 ) 
                               
                               ⁢ 
                               cos 
                               ⁢ 
                               
                                 θ 
                                 c 
                               
                             
                             + 
                             
                               2 
                               ⁢ 
                               
                                 I 
                                 b 
                               
                               ⁢ 
                               
                                 K 
                                 ⁡ 
                                 ( 
                                 
                                   λ 
                                   , 
                                   x 
                                   , 
                                   y 
                                 
                                 ) 
                               
                               ⁢ 
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                               ⁢ 
                               
                                 θ 
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                         = 
                           
                         
                           
                             
                               I 
                               c 
                             
                             ⁢ 
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                             ⁢ 
                             
                               θ 
                               c 
                             
                           
                           
                             
                               
                                 I 
                                 c 
                               
                               ⁢ 
                               cos 
                               ⁢ 
                               
                                 θ 
                                 c 
                               
                             
                             + 
                             
                               2 
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                                 I 
                                 b 
                               
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                               ⁢ 
                               
                                 θ 
                                 b 
                               
                             
                           
                         
                       
                     
                   
                 
               
               
                 
                   ( 
                   4 
                   ) 
                 
               
             
           
         
       
     
     It can be said that the feature shown in Expression 4 is a feature that is independent of the reflection coefficient K, and for which the color dependence is dissolved. In addition, the feature calculation unit  303  converts the feature indicated in Expression 4 into a one-dimensional vector, and performs conversion of sorting the values of respective pixels in ascending order or descending order. Accordingly, the larger the light diffuse reflection that occurs on the surface of a face is, the larger the value of the obtained feature is, and thus the three-dimensional shape of the face is reflected on the obtained feature. 
     According to the third example embodiment, the spoofing determination unit  304  determines the authenticity using the integrated first feature and second feature. Specifically, according to the third example embodiment, different features are calculated based on a plurality of regions of a face using face information, and authenticity is determined based on a feature obtained by integrating these obtained features. 
     [Apparatus Operations] 
     Next, operations of the spoofing detection apparatus according to the third example embodiment of the invention will be described with reference to  FIG. 8 .  FIG. 8  is a flowchart showing operations of the spoofing detection apparatus according to the third example embodiment of the invention. In the following description,  FIG. 6  will be referred to as appropriate. In addition, according to the third example embodiment, the spoofing detection method is carried out as a result of causing the spoofing detection apparatus to operate. Thus, a description of the spoofing detection method according to the third example embodiment is replaced with the following description of operations of the spoofing detection apparatus. 
     Note that, also in the example in  FIG. 8 , similarly to the example in  FIG. 7 , an image of the face of a subject person when a flash is on and an image when the flash is off are shot. In addition, the flash illumination time is 300 milliseconds, and one image is shot in 150 milliseconds after flash illumination is started, and another image is shot in 150 milliseconds after the flash is turned off. 
     As shown in  FIG. 8 , first, when the terminal apparatus  500  is instructed to perform authentication, the shooting control unit  305  instructs the light-emitting apparatus  320  to emits light at the same time as shooting (step C 1 ), and also instructs the image capture apparatus  310  to perform shooting (step C 2 ). 
     When step C 2  is executed, shooting is performed by the image capture apparatus  310 , and image data is output, and thus the face image obtaining unit  301  obtains the output image data as a first image frame (step C 3 ). 
     Next, after step C 3  is executed, the shooting control unit  305  instructs the light-emitting apparatus  320  to turn off (step C 4 ), and also instructs the image capture apparatus  310  to perform shooting (step C 5 ). 
     When step C 5  is executed, shooting is performed by the image capture apparatus  310 , and image data is output, and thus the face image obtaining unit  301  obtains the output image data as a second image frame (step C 6 ). 
     Next, the face information extraction unit  302  extracts information specifying a face portion of the subject person as first face information, from the first image frame obtained in step C 3 , and extracts information specifying a face portion of the subject person as second face information, from the second image frame obtained in step C 6  (step C 7 ). 
     Next, the feature calculation unit  303  extracts a portion that includes a bright point, from the first image frame, based on the first face information, and extracts a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information. The feature calculation unit  303  then calculates, based on the two extracted portions, a feature that is independent of the position of the bright point (step C 8 ). 
     The above steps C 1  to C 8  are similar to steps B 1  to B 8  according to the second example embodiment shown in  FIG. 7 , and similar processes are performed in these steps. However, according to the third example embodiment, step C 9  is executed in parallel to or before/after step C 8 . 
     In step C 9 , the feature calculation unit  303  calculates a second feature that reflects the three-dimensional shape of the face, based on diffuse reflection on the face of the subject person. Specifically, the feature calculation unit  303  specifies a first face region from the first image data based on the first face information, and also specifies a second face region from the second image data based on the second face information. The feature calculation unit  303  then obtains the difference between luminance distribution of the first face region and luminance distribution of the second face region, and calculates a second feature based on the obtained difference. 
       FIG. 9  is a diagram showing an example of a feature calculated based on an iris region and a feature calculated based on a face region according to the third example embodiment. As shown in  FIG. 9 , according to the third example embodiment, features calculated based on iris regions and features calculated based on face regions are obtained. In  FIG. 9 , reference numeral  701  denotes a feature vector calculated based on an iris region of a real face, and reference numeral  702  denotes a feature vector calculated based on an iris region of a fake face. 
     Next, the feature calculation unit  303  integrates the feature obtained in step C 8  and the feature obtained in step C 9  (step C 10 ). Specifically, the features have been converted into a one-dimensional vector, and thus two features are integrated into one vector. 
     Next, the spoofing determination unit  304  determines the authenticity of the subject person captured by the image capture apparatus  310 , based on the features integrated in step C 10  (step C 11 ). Specifically, the spoofing determination unit  304  determines whether or not the captured subject person is a real human. Step C 10  is similar to step B 9  shown in  FIG. 7 . 
     The spoofing determination unit  304  then presents the result of the determination (detection result) in step B 9 , on a screen using the display device  330  of the terminal apparatus  500  (step C 12 ). Step C 12  is similar to step B 10  shown in  FIG. 7 . 
     Accordingly, also in the third example embodiment, the user of the terminal apparatus  500  can confirm the detection result. In addition, if the detection result indicates that the subject person is a real human, the terminal apparatus  500  continues authentication processing, and, if the detection result indicates that the subject person is not a real human, the terminal apparatus  500  stops authentication processing. 
     Effect of Third Example Embodiment 
     As described above, according to the third example embodiment, two regions where different forms of reflection occur, namely an iris region in which light from the light-emitting apparatus  320  is specularly reflected and a face region in which light from the light-emitting apparatus  320  is diffusely reflected are combined, and thereby a feature is calculated. Authenticity is then determined based on the feature obtained through this combination, and thus, according to the third example embodiment, more accurate spoofing detection is enabled. 
     [Program] 
     The program according to the third example embodiment may be a program for causing a computer to execute steps C 1  to C 12  shown in  FIG. 8 . The spoofing detection apparatus and the spoofing detection method according to the third example embodiment can be realized as a result of installing this program to a computer, and executing this program. In this case, the processor of the computer functions as the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , the spoofing determination unit  304 , and the shooting control unit  305 , and performs processing. 
     In addition, the program according to the third example embodiment may also be executed by a computer system constituted by a plurality of computers. In this case, for example, each of the computers may also function as one of the face image obtaining unit  301 , the face information extraction unit  302 , the feature calculation unit  303 , the spoofing determination unit  304 , and the shooting control unit  305 . 
     Modified Examples of Example Embodiments 
     According to the above third example embodiment, the spoofing determination unit  304  can separately execute authenticity determination that is based on the feature calculated in step C 8  and authenticity determination that is based on the feature calculated in step C 9 . In this case, the spoofing determination unit  304  performs determination based on the two authenticity determination results in a comprehensive manner, and conclusively determines whether or not spoofing has occurred. 
     Specifically, the spoofing determination unit  304  calculates a score that indicates the possibility of being authentic (true/false value) every time authenticity determination is performed, and, for example, the spoofing determination unit  304  obtains the average value of two scores, and makes a determination of true (a real human) if the average value exceeds a fixed value. 
     In addition, according to the above second and three example embodiments, one image of a face is shot when the light-emitting apparatus  320  is emitting light and another image of the face is shot when the light-emitting apparatus  320  is turned off, as still images, and the light-emitting period is 300 milliseconds, and shooting timings are set to 150 milliseconds from when light is emitted and 150 milliseconds after light is turned off. Note that these settings are exemplary, and may be changed. The shooting control unit  305  can change the settings in accordance with a value input to the terminal apparatus  500  by the user, for example. 
     In addition, in the above first to third example embodiments, shooting that is performed by the image capture apparatus  310  is performed in a state where the face of a subject person is stationary. This is because the face of the subject person needs to be extracted from an image. Therefore, during shooting, it is preferable to prompt the subject person to not move their face. Therefore, for example, before giving an instruction to perform shooting, the face image obtaining unit  301  preferably displays, on the display screen of the display device or the like, a message for prompting the subject person to not move their face. 
     (Physical Configuration) 
     Here, a computer that realizes a spoofing detection apparatus by executing the program according to one of the first to third example embodiments will be described with reference to  FIG. 10 .  FIG. 10  is a block diagram showing an example of a computer that realizes the spoofing detection apparatus according to one of the first to third example embodiments of the invention. 
     A computer  400  shown in  FIG. 10  is, for example, a computer incorporated in a mobile terminal apparatus such as a mobile phone or a smartphone. As shown in  FIG. 10 , the computer  400  includes a processor  401 , a memory  402 , a storage  403 , an input/output interface (input/output I/F)  404 , and a communication interface (communication I/F)  405 . The processor  401 , the memory  402 , the storage  403 , the input/output interface  404 , and the communication interface  405  are connected by a data transmission path (bus)  406  for mutually transmitting/receiving data. Note that the hardware configuration of the computer  400  is not limited to the configuration shown in  FIG. 10 . 
     The processor  401  is a computation processing apparatus such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The memory  402  is a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The storage  403  is a storage apparatus such as an HDD (Hard Disk Drive), an SSD (Solid State Drive), or a memory card. 
     The memory  402  or the storage  403  stores a program for realizing the units that constitute a spoofing detection apparatus. As a result of the processor  401  executing the program, the units are realized, and various types of processing are executed. Here, a configuration may also be adopted in which, when executing the program, the processor  401  reads out the program to the memory  402  and then executes the program, or executes the program without reading out the program to the memory  402 . 
     A configuration may also be adopted in which the above-described program is stored in one of various types of non-transitory computer-readable recording media, and is supplied to the computer  400 . Examples of the non-transitory computer-readable recording medium include various types of tangible recording media. 
     Examples of the non-transitory computer-readable recording medium include a magnetic recording medium (such as a flexible disk, a magnetic tape, or a hard disk drive), a magnetooptical recording medium (such as a magnetooptical disk), a CD-ROM (compact disc read only memory), a CD-R (compact disc recordable), a CD-R/W (compact disc rewritable), and a semiconductor memory (such as a mask ROM, a PROM (programmable ROM), an EPROM (erasable PROM), a flash ROM, or a RAM). 
     In addition, the program may also be supplied to the computer  400  from one of various types of transitory computer-readable recording media. Examples of the transitory computer-readable recording medium include an electrical signal, an optical signal, and electromagnetic waves. The transitory computer-readable recording medium can supply the program to the computer via a wired communication path or a wireless communication path made of an electric wire, an optical fiber, or the like. 
     The input/output interface  404  is connected to the image capture apparatus  310 , the display device  330 , the input device  340 , and the like. The display device  330  is a device for displaying a screen in accordance with rendering data processed by the processor  401 , such as an LCD (Liquid Crystal Display) or a CRT (Cathode Ray Tube) display. The communication interface  405  transmits/receives data to/from an external apparatus. The communication interface  405  communicates with an external apparatus via a wired network or a wireless network, for example. 
     The image capture apparatus  310  is an apparatus for the user to shoot the face of a subject person, etc., or a subject person to shoot their own face, etc., such as a digital camera or a digital video camera. The input device  340  is a device for receiving a user&#39;s operation input, and is a keyboard, a touch sensor, a touch panel, or the like. For example, if the input device  340  is a touch panel, the input device  340  and the display device  330  may be integrated. 
     Note that the spoofing detection apparatus according to the example embodiment can also be realized by using items of hardware respectively corresponding to the units, instead of a computer in which the program is installed. Furthermore, a configuration may also be adopted in which a portion of the spoofing detection apparatus is realized by the program, and the remaining portion is realized by hardware. 
     The example embodiments described above can be partially or wholly realized by supplementary notes 1 to 12 described below, but the invention is not limited to the following description. 
     (Supplementary Note 1) 
     A spoofing detection apparatus comprising:
         a face image obtaining unit configured to obtain, from an image capture apparatus, a first image frame that includes a face of a subject person when light was emitted from a light-emitting apparatus associated with the image capture apparatus and a second image frame that includes the face of the subject person when the light-emitting apparatus was turned off;   a face information extraction unit configured to extract information specifying a face portion of the subject person as first face information, from the first image frame, and extract information specifying a face portion of the subject person as second face information, from the second image frame;   a feature calculation unit configured to extract a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, from the first image frame, based on the first face information, also extract a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information, and calculate, based on the two extracted portions, a feature that is independent of a position of the bright point; and   a spoofing determination unit configured to determine authenticity of the subject person captured by the image capture apparatus, based on the feature.       

     (Supplementary Note 2) 
     The spoofing detection apparatus according to Supplementary Note 1, further comprising:
         a shooting control unit configured to set a light-emitting period of the light-emitting apparatus and a shooting timing of the image capture apparatus.       

     (Supplementary Note 3) 
     The spoofing detection apparatus according to Supplementary Note 1 or 2,
         wherein the feature calculation unit calculates a second feature that reflects a three-dimensional shape of the face of the subject person, in addition to the feature that is independent of the position of the bright point, and   the spoofing determination unit determines authenticity of the subject person captured by the image capture apparatus, based on the feature that is independent of the position of the bright point and the second feature.       

     (Supplementary Note 4) 
     The spoofing detection apparatus according to Supplementary Note 3,
         wherein the spoofing determination unit separately executes authenticity determination that is based on the feature that is independent of the position of the bright point and authenticity determination that is based on the second feature, calculates a score that indicates a possibility of being authentic every time authenticity determination is performed, and executes conclusive authenticity determination based on scores calculated in the respective instances of authenticity determination.       

     (Supplementary Note 5) 
     A spoofing detection method comprising:
         (a) a step of obtaining, from an image capture apparatus, a first image frame that includes a face of a subject person when light was emitted from a light-emitting apparatus associated with the image capture apparatus and a second image frame that includes the face of the subject person when the light-emitting apparatus was turned off;   (b) a step of extracting information specifying a face portion of the subject person as first face information, from the first image frame, and extracting information specifying a face portion of the subject person as second face information, from the second image frame;   (c) a step of extracting a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, from the first image frame, based on the first face information, also extracting a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information, and calculating, based on the two extracted portions, a feature that is independent of a position of the bright point; and   (d) a step of determining authenticity of the subject person captured by the image capture apparatus, based on the feature.       

     (Supplementary Note 6) 
     The spoofing detection method according to Supplementary Note 5, further comprising:
         (e) a step of setting a light-emitting period of the light-emitting apparatus and a shooting timing of the image capture apparatus.       

     (Supplementary Note 7) 
     The spoofing detection method according to Supplementary Note 5 or 6,
         wherein, in the (c) step, a second feature that reflects a three-dimensional shape of the face of the subject person is calculated, in addition to the feature that is independent of the position of the bright point, and   in the (d) step, authenticity of the subject person captured by the image capture apparatus is determined based on the feature that is independent of the position of the bright point and the second feature.       

     (Supplementary Note 8) 
     The spoofing detection method according to Supplementary Note 7,
         wherein, in the (d) step, authenticity determination that is based on the feature that is independent of the position of the bright point and authenticity determination that is based on the second feature are separately executed, a score that indicates a possibility of being authentic is calculated every time authenticity determination is performed, and conclusive authenticity determination is executed based on scores calculated in the respective instances of authenticity determination.       

     (Supplementary Note 9) 
     A computer-readable recording medium that includes a program recorded thereon, the program including instructions that cause a computer to carry out:
         (a) a step of obtaining, from an image capture apparatus, a first image frame that includes a face of a subject person when light was emitted from a light-emitting apparatus associated with the image capture apparatus and a second image frame that includes the face of the subject person when the light-emitting apparatus was turned off;   (b) a step of extracting information specifying a face portion of the subject person as first face information, from the first image frame, and extracting information specifying a face portion of the subject person as second face information, from the second image frame;   (c) a step of extracting a portion that includes a bright point formed by reflection in an iris region of an eye of the subject person, from the first image frame, based on the first face information, also extracting a portion corresponding to the portion that includes the bright point, from the second image frame, based on the second face information, and calculating, based on the two extracted portions, a feature that is independent of a position of the bright point; and   (d) a step of determining authenticity of the subject person captured by the image capture apparatus, based on the feature.       

     (Supplementary Note 10) 
     The computer-readable recording medium according to Supplementary Note 9, the program further including an instruction that causes a computer to carry out:
         (e) a step of setting a light-emitting period of the light-emitting apparatus and a shooting timing of the image capture apparatus.       

     (Supplementary Note 11) 
     The computer-readable recording medium according to Supplementary Note 9 or 10,
         wherein, in the (c) step, a second feature that reflects a three-dimensional shape of the face of the subject person is calculated, in addition to the feature that is independent of the position of the bright point, and   in the (d) step, authenticity of the subject person captured by the image capture apparatus is determined based on the feature that is independent of the position of the bright point and the second feature.       

     (Supplementary Note 12) 
     The computer-readable recording medium according to Supplementary Note 11,
         wherein, in the (d) step, authenticity determination that is based on the feature that is independent of the position of the bright point and authenticity determination that is based on the second feature are separately executed, a score that indicates a possibility of being authentic is calculated every time authenticity determination is performed, and conclusive authenticity determination is executed based on scores calculated in the respective instances of authenticity determination.       

     Although the present invention has been described above with reference to the example embodiments above, the invention is not limited to the above example embodiments. Various modifications understandable to a person skilled in the art can be made in configurations and details of the invention, within the scope of the invention. 
     INDUSTRIAL APPLICABILITY 
     As described above, according to the invention, during face authentication, spoofing detection can be executed without being affected by dependence on the position of a reflection bright point. The invention is useful for various systems in which face authentication is performed. 
     LIST OF REFERENCE SIGNS 
     
         
         
           
               101  User 
               102  Terminal apparatus equipped with camera when flash is on 
               103  Terminal apparatus equipped with camera when flash is off 
               105  Image when flash is on 
               106  Image when flash is off 
               201 ,  202  Portion of image of iris region 
               203 ,  204  Conventional feature calculated based on iris region 
               205 ,  206  feature calculated based on iris region according to present invention 
               300  Spoofing detection apparatus (first example embodiment) 
               301  Face image obtaining unit 
               302  Face information extraction unit 
               303  feature calculation unit 
               304  Spoofing determination unit 
               305  Shooting control unit 
               310  Image capture apparatus 
               320  Light-emitting apparatus 
               330  Display device 
               340  Input device 
               350  Spoofing detection apparatus (second example embodiment) 
               400  Computer 
               401  Processor 
               402  Memory 
               403  Storage 
               404  Input/output interface (Input/output I/F) 
               500  Terminal apparatus 
               701  Feature vector calculated based on iris region of real face 
               702  Feature vector calculated based on iris region of fake face