Patent Publication Number: US-8983235-B2

Title: Pupil detection device and pupil detection method

Description:
TECHNICAL FIELD 
     The present invention relates to a pupil detection apparatus and a pupil detection method. 
     BACKGROUND ART 
     When a pupil is detected on an image, error detection may occur frequently because resolution in a pupil part is too low. For example, error detection occurs when a field angle of an imaging apparatus is increased for taking a picture of a wide range and resolution in an eye area cannot be secured sufficiently. 
     In a typical pupil detection method based on an image, there is utilized a first feature that brightness of a pupil part is lower than brightness of a periphery of the pupil part, or a second feature that a pupil has a circular or ellipsoidal shape. However, when resolution cannot be secured sufficiently, sometimes the contour of the pupil on the image has a polygonal shape and does not have the circular or ellipsoidal shape. When the pupil detection is performed in this situation using the above described second feature, error detection occurs frequently. There are many parts each having a low brightness comparable with that of the pupil part on the image around an eye although the shape thereof is not actually circular or ellipsoidal, such as eyelashes, an iris contour, a shadow caused at an eye tail and an eye inner corner, or noise generated when an S/N ratio is poor. Then, when resolution is low, such a part having a low brightness comparable with that of the pupil part is detected erroneously as the pupil, although the shape thereof is different from the shape of the pupil. 
     For this problem, there has been proposed the following techniques. For example, in a technique disclosed in Patent Literature 1, an eye area is detected from a face image, and zoom processing is performed on the detected eye area. Then, an image of the eye area enlarged so that the edge of a pupil may be observed sufficiently is obtained and thereby a resolution of the pupil necessary for the pupil detection is secured. 
     Further, there is a technique not for the pupil detection, but as a technique, which is disclosed in Patent Literature 2, for detecting an iris which is a part of an eye. In the technique disclosed in Patent Literature 2, an iris contour is preliminarily detected from an eye area and the image of the eye area is converted so that the iris contour has a circular shape of a predetermined size. 
     CITATION LIST 
     Patent Literature 
     
         
         PTL 1 
         Japanese Patent Application Laid-Open No. 2002-282210 
         PTL 2 
         Japanese Patent Application Laid-Open No. 2008-90483 
       
    
     SUMMARY OF INVENTION 
     Technical Problem 
     However, in the technique disclosed in Patent Literature 1, the size of the pupil to be detected is not known in the stage of zoom processing for the eye area, and therefore it is difficult to set a zoom scale factor thereof to an optimum value for edge detection to detect the pupil. 
     Accordingly, for performing the pupil detection stably, it is necessary to always set the zoom scale factor large enough to detect the pupil contour as an edge even when the pupil becomes the smallest (e.g., case of a pupil when light is too bright). 
     That is, when the zoom scale factor is not large enough, the number of pixels in the edge of the pupil contour part decreases for a small pupil and the pupil detection becomes unstable. Therefore, it is necessary to set the zoom scale factor so that a sufficient number of pixels may be secured in the edge even for the small pupil. 
     However, when the zoom scale factor is set so that a sufficient number of pixels may be secured in the edge even for the small pupil, the number of edge pixels excessively larger than an essentially required number of edge pixels is detected for a large pupil. In this case, since pixels, the number of which is larger than that required for a detection performance, are to be processed, there arises a problem that a calculation amount is increased for the pupil detection processing. 
     Further, in the technique disclosed in Patent Literature 2, the iris contour shape on the image is necessary as a conversion parameter when the eye area image is converted. Accordingly, even when this technique is to be applied to the pupil detection processing, a pupil detection result is necessary for the pupil detection and thus it is difficult to apply this technique thereto. 
     A purpose of the present invention is to provide a pupil detection apparatus and a pupil detection method which can improve pupil detection accuracy even when an image to be detected has a low resolution. 
     Solution to Problem 
     A pupil detection apparatus according to one aspect of the present invention is a pupil detection apparatus that detects an image of a pupil, and includes an acquisition section that acquires an actual scale value of a peripheral area including the pupil; a first calculation section that calculates an actual scale prediction value of a pupil diameter; a second calculation section that calculates a target value of resolution on the basis of the calculated actual scale prediction value; a normalization section that calculates a scale-up/scale-down factor on the basis of the calculated target value of the resolution and the actual scale value of the peripheral area, and normalizes an image of the peripheral area on the basis of the calculated scale-up/scale-down factor; and a detection section that detects the image of the pupil from the normalized image of the peripheral area. 
     A pupil detection method according to one aspect of the present invention is a pupil detection method that detects an image of a pupil, and includes the steps of acquiring an actual scale value of a peripheral area including the pupil; calculating an actual scale prediction value of a pupil diameter; calculating a target value of resolution on the basis of the calculated actual scale prediction value; calculating a scale-up/scale-down factor on the basis of the calculated target value of the resolution and the actual scale value of the peripheral area; normalizing an image of the peripheral area on the basis of the calculated scale-up/scale-down factor; and detecting the image of the pupil from the normalized image of the peripheral area. 
     Advantageous Effects of Invention 
     According to the present invention, it is possible to provide a pupil detection apparatus and a pupil detection method which can improve pupil detection accuracy even when an image to be detected has a low resolution. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram showing a configuration of a pupil detection apparatus according to Embodiment 1 of the present invention; 
         FIG. 2  is a block diagram showing a configuration of an eye area detection section; 
         FIG. 3  is a flowchart for explaining operation of a pupil detection apparatus; 
         FIG. 4  is a diagram showing a face image which is a target image; 
         FIGS. 5A and 5B  are diagrams showing an example of a resolution table; 
         FIG. 6  is a block diagram showing a configuration of a pupil detection apparatus according to Embodiment 2 of the present invention; and 
         FIG. 7  is a block diagram showing a configuration of a pupil detection apparatus according to Embodiment 3 of the present invention. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Hereinafter, embodiments of the present invention will be explained in detail with reference to the drawings. Note that, in the embodiments, the same constituent is denoted by the same sign and explanation thereof will be omitted to avoid duplication. 
     Embodiment 1 
     Configuration of a Pupil Detection Apparatus 
       FIG. 1  is a block diagram showing a configuration of pupil detection apparatus  100  according to Embodiment 1 of the present invention. Pupil detection apparatus  100  is provided, for example, inside a car and connected to a line-of-sight detection apparatus for use. This line-of-sight detection apparatus determines a pupil position on the basis of a detection result of pupil detection apparatus  100 , and detects the line-of-sight direction of a driver. Hereinafter, in particular, there will be explained a case in which pupil detection apparatus  100  is applied to the line-of-sight detection apparatus. 
     In  FIG. 1 , pupil detection apparatus  100  includes eye area image acquisition section  101 , eye area actual size calculation section  102 , pupil state prediction section  103 , actual size pupil diameter storage section  104 , necessary resolution estimation section  105 , table storage section  106 , eye area image normalization section  107 , pupil detection section  108 , and pupil actual size calculation section  109 . 
     Eye area image acquisition section  101  acquires an eye area image and outputs it to eye area actual size calculation section  102 . 
     Specifically, eye area image acquisition section  101  includes image input section  111  and eye area detection section  112 . 
     Image input section  111  captures an image of an imaging target (i.e., person, here). Here, image input section  111  includes a stereo camera and acquires a stereo image with the stereo camera. This target image data is output to eye area detection section  112 . 
     Image input section  111  is disposed at a position in front of a driving seat such as a position on a steering wheel or a dashboard in the car. Thereby, image input section  111  photographs a face of a driver during driving. 
     Eye area detection section  112  detects an eye area image from the target image acquired from image input section  111 . 
     Specifically, eye area detection section  112  includes face detection section  121 , facial part detection section  122 , and eye area determination section  123 , as shown in  FIG. 2 . 
     Face detection section  121  detects a face image from the target image acquired from image input section  111  and outputs detected face image data to facial part detection section  122 . 
     Facial part detection section  122  detects a facial part group (i.e., mouth corner, eye tail, eye inner corner, etc.) from the face image data acquired from face detection section  121 , and outputs positional coordinates of each facial part together with the face image data to eye area determination section  123 . 
     Eye area determination section  123  acquires the positional coordinates of each facial part from facial part detection section  122 , and determines a position and sizes (width and height) of an eye area in the face image on the basis of the acquired positional coordinates of each facial part. Then, eye area determination section  123  cuts out an image of the eye area from the face image as an eye area image. The position and sizes of the eye area in the face image are output to eye area actual size calculation section  102  as an eye area detection result together with the eye area image. Note that the position and sizes of the eye area are calculated for each of the right eye and the left eye. 
     Returning to  FIG. 1 , eye area actual size calculation section  102  calculates an actual scale value of the eye area on the basis of the eye area image data acquired from eye area image acquisition section  101  (stereo image data in Embodiment 1) and the eye area detection result. The actual scale value of the eye area is a value expressing what actual size the eye area has on the target image. The actual scale value of the eye area is expressed by an actual size (e.g., 30 mm in width or 20 mm in height) of a photographed object (eye peripheral part of the face) as a width or a height of the eye area, or a distance per one pixel on the eye area image (e.g., 0.75 mm per pixel), for example. 
     Pupil state prediction section  103  calculates an actual scale prediction value of a pupil diameter. Specifically, pupil state prediction section  103  predicts an actual size of a pupil in the eye area image acquired in eye area image acquisition section  101 , on the basis of a past actual size pupil diameter retained in actual size pupil diameter storage section  104 , and calculates the actual scale prediction value. 
     Actual size pupil diameter storage section  104  stores a pupil actual size acquired from pupil actual size calculation section  109  together with photographing time. That is, actual size pupil diameter storage section  104  retains a pupil diameter (history thereof) derived from the pupil image acquired in the past by eye area image acquisition section  101 . 
     Necessary resolution estimation section  105  calculates a target value of resolution on the basis of the actual scale prediction value calculated in pupil state prediction section  103 . In the calculation of the target value of resolution, a resolution table stored in table storage section  106  is used. In the resolution table, an actual scale value candidate group of the pupil diameter and an image resolution necessary for pupil detection in each of the actual scale value candidates are associated with each other. Accordingly, necessary resolution estimation section  105  calculates a target value of the resolution on the basis of the actual scale prediction value calculated in pupil state prediction section  103  and the necessary resolution corresponding to the actual scale prediction value using the resolution table. 
     Table storage section  106  retains the above described resolution table. The resolution table is a table associating a plurality of pupil diameters with a resolution which is calculated preliminarily by experiment, simulation or the like and necessary for stably detecting the pupil having each of the pupil diameters. The resolution table is generated, for example, by a process of photographing an image of each pupil diameter in a plurality of resolutions, selecting a resolution providing the best pupil detection result in the images of the respective resolutions, and associating the resolution with the pupil diameter as a pupil resolution of each pupil diameter. 
     Eye area image normalization section  107  calculates a scale-up/scale-down factor on the basis of the resolution target value calculated in necessary resolution estimation section  105  and the eye area actual scale value calculated in eye area actual size calculation section  102 . Specifically, eye area image normalization section  107  calculates the number of pixels per unit length on the basis of the eye area actual scale value calculated in eye area actual size calculation section  102  and the number of pixels used for the eye area image acquired from eye area image acquisition section  101 , and calculates the scale-up/scale-down factor by obtaining a ratio of the calculated number of pixels per unit length and the resolution target value calculated in necessary resolution estimation section  105 . 
     Then, eye area image normalization section  107  normalizes the eye area image acquired from eye area image acquisition section  101  on the basis of the calculated scale-up/scale-down factor. The eye area image normalized here (i.e., normalized eye area image) is output to pupil detection section  108 . 
     Further, eye area image normalization section  107  calculates an actual size value of the eye area in the normalized eye area image and outputs the actual size value to pupil actual size calculation section  109 . 
     Pupil detection section  108  detects a pupil image from the normalized eye area image acquired from eye area image normalization section  107 . Coordinates of a pupil center and a pupil diameter in the detected pupil image are output to a line-of-sight detection section (not shown in the drawing) and pupil actual size calculation section  109 , respectively. 
     Pupil actual size calculation section  109  calculates a pupil actual size from the eye area actual size value in the normalized eye area image acquired from eye area image normalization section  107  and the pupil diameter acquired from pupil detection section  108 . This actual size pupil diameter is retained in actual size pupil diameter storage section  104 . 
     Operation of Pupil Detection Apparatus  100   
     Operation of pupil detection apparatus  100  having the above configuration will be explained.  FIG. 3  is a flowchart for explaining the operation of pupil detection apparatus  100 . The flowchart of  FIG. 3  includes a processing flow in the above described line-of-sight detection apparatus. 
     The processing flow shown in  FIG. 3  starts together with the start of photographing work. The photographing work may be started by user operation or may be started with any external signal as a trigger. 
     &lt;Image Acquisition Processing&gt; 
     In step S 201 , image input section  111  captures an image of an imaging target (i.e., person, here). Thereby, a target image is acquired. 
     Image input section  111  is a digital camera provided with a CMOS image sensor and a lens, for example. Accordingly, an image which is captured in image input section  111  and has the PPM (Portable Pix Map file format) format or the like is temporarily stored in an unillustrated image storage section (e.g., memory space of a PC) which is included in image input section  111 , and then output to eye area detection section  112 , while keeping the PPM format. 
     &lt;Face Image Detection Processing&gt; 
     In step S 202 , face detection section  121  detects a face image from the target image acquired from image input section  111 .  FIG. 4  is a diagram showing the face image as the target image. Note that, in the captured face image, an image horizontal direction is assumed to be an X axis, an image vertical direction is assumed to be a Y axis, and one pixel is assumed to correspond to one coordinate point, for example. 
     The face area detection processing, for example, extracts a candidate for characteristic image (i.e., characteristic image candidate) from the target image, compares the extracted characteristic image candidate with a preliminarily prepared characteristic image expressing a face area, and thereby detects a characteristic image candidate having a high similarity. The similarity is obtained by a method of collating a preliminarily acquired Gabor feature amount of an average face and a Gabor feature amount extracted by scanning the target image, and calculating an inverse of an absolute value of difference therebetween, for example. 
     In this case, face detection section  121  extracts a face area candidate group in image  400  of  FIG. 4 , compares the extracted face area candidate group with a preliminarily prepared template, and detects a face area candidate having the highest correlation as face image  401 . Note that the face area detection processing may be performed by detecting a flesh color area from within the image (i.e., flesh color area detection), by detecting an ellipsoidal part (i.e., ellipsoid detection), or by using a statistical pattern recognition method. Any other method may be employed if the technique can perform the above described face detection. 
     &lt;Facial Part Detection Processing&gt; 
     In step S 203 , facial part detection section  122  detects a facial part group (i.e., mouth corner, eye tail, eye inner corner, etc.) from the face image acquired from face detection section  121 , and outputs positional coordinates of each facial part to eye area determination section  123 . A search area of the facial part group is face image  401  specified in step S 202 .  FIG. 4  shows each part of facial part group  402 . 
     The facial part group detection processing detects two-dimensional coordinates of an end point of a facial part such as a mouth corner, eye tail, and eye inner corner, a nostril, or the like using a separability filter, for example. Further, a learning section is caused to preliminarily learn an association relationship between a plurality of face images and facial part positions corresponding to the face images, and facial part detection section  122  may detect a part having the highest likelihood in the association relationship as a facial part when face image  401  is input. Alternatively, facial part detection section  122  may search face image  401  for a facial part using a template of a typical facial part. 
     &lt;Eye Area Determination Processing&gt; 
     In step S 204 , eye area determination section  123  determines an eye area from the face image acquired from face detection section  121  and the facial part group acquired from facial part detection section  122 . 
     The eye area determination processing determines rectangular area  403  including an eye tail and eye inner corner as an eye area for each of the right and left eyes, for example, and acquires left-and-upper end point coordinates and right-and-lower end point coordinates of the rectangle as an eye area detection result. Here, the left-and-upper end point coordinates and the right-and-lower end point coordinates of the rectangle are used as a parameter showing a position and a size of the eye area. 
     &lt;Eye Area Actual Size Calculation Processing&gt; 
     In step S 205 , eye area actual size calculation section  102  calculates an actual scale value of the eye area from eye area image data (stereo image data in Embodiment 1) acquired from eye area image acquisition section  101 . Specifically, eye area actual size calculation section  102  calculates a feature distance (number of pixels) p between feature points on the image from the eye area image data. This feature distance between the feature points on the image is a distance between an eye tail and an eye inner corner on the image, for example. Then, eye area actual size calculation section  102  calculates x/p by divided reference distance x by the feature distance p. Reference distance x is an average distance between the eye tail and the eye inner corner (e.g., 28 mm), for example, in a real space. Therefore, x/p expresses an actual size value corresponding to one pixel. 
     &lt;Estimated Pupil Diameter Calculation Processing&gt; 
     In step S 206 , pupil state prediction section  103  calculates an actual scale prediction value of a pupil diameter. 
     Specifically, pupil state prediction section  103  predicts an actual size of a pupil included in the eye area image acquired from eye area image acquisition section  101  on the basis of a past actual size pupil diameter retained in actual size pupil diameter storage section  104 . For example, pupil state prediction section  103  calculates actual scale prediction value D t  of the pupil diameter by equation 1 when an actual size pupil diameter one-frame previous is denoted by D t-1  and an actual size pupil diameter two-frame previous is denoted by D t-2 .
 
[1]
 
 D   t   =D   t-1 +( D   t-1   −D   t-2 )  (Equation 1)
 
     Alternatively, pupil state prediction section  103  may calculate actual scale prediction value D t  of the pupil diameter by equation 2. In equation 2, V m  is an average human miosis (here, indicating that a pupil becomes small) rate.
 
[2]
 
 D   t   =D   t-1   +V   m (( t −( t− 1))  (Equation 2)
 
     Alternatively, pupil state prediction section  103  may perform the state prediction using a Kalman filter or the like. 
     &lt;Necessary Resolution Calculation Processing&gt; 
     In step S 207 , necessary resolution estimation section  105  calculates a resolution target value on the basis of the actual scale prediction value calculated in pupil state prediction section  103 . The calculation of the resolution target value uses the resolution table stored in table storage section  106 . This resolution table associates an actual scale value candidate group of the pupil diameter and image resolutions necessary for the pupil detection in the respective actual scale value candidates. 
     The resolution table stored in table storage section  106  may be retained in a graph format as shown in  FIG. 5A  or may be retained in a table format as shown in  FIG. 5B . A tendency characteristic of the resolution table is as follows. (1) As an actual size pupil diameter (i.e., actual scale value candidate) is smaller, a value of the corresponding necessary resolution becomes larger. (2) The necessary resolution decreases monotonically to the actual scale value candidate and converges to a certain value. 
     Specifically, necessary resolution estimation section  105  calculates resolution target value b/a on the basis of actual scale prediction value a calculated in pupil state prediction section  103  and necessary resolution b corresponding to the actual scale prediction value, using the resolution table. Resolution target value b/a is the number of pixels per actual size unit length, which is necessary to stably detect the pupil having a predicted pupil diameter. 
     &lt;Eye Area Image Normalization Processing&gt; 
     In step S 208 , eye area image normalization section  107  calculates a scale-up/scale-down factor on the basis of the resolution target value calculated in necessary resolution estimation section  105  and the eye area actual scale value calculated in eye area actual size calculation section  102 . Specifically, eye area image normalization section  107  calculates the number of pixels per unit length on the basis of the eye area actual scale value calculated in eye area actual size calculation section  102  and the number of pixels used in the eye area image acquired from eye area image acquisition section  101 , and calculates the scale-up/scale-down factor by obtaining a ratio of the calculated number of pixels per unit length and the resolution target value calculated in necessary resolution estimation section  105 . 
     Then, eye area image normalization section  107  normalizes the eye area image acquired from eye area image acquisition section  101  on the basis of the calculated scale-up/scale-down factor. This scale-up/scale-down processing uses a method used in typical image processing such as a bilinear method and a bicubic method. 
     &lt;Pupil Search Processing&gt; 
     In step S 209 , pupil detection section  108  detects a pupil image from the normalized eye area image acquired from eye area image normalization section  107 . Pupil center coordinates and a pupil diameter in the pupil image are output to the line-of-sight detection section (not shown in the drawing) and pupil actual size calculation section  109 , respectively. 
     In step S 210 , the line-of-sight detection section (not shown in the drawing) calculates a line-of-sight direction from a face direction vector expressing a face front direction which is calculated from the coordinates of facial part group  402  and a line-of-sight direction vector relative to the face front direction which is calculated from the coordinates of the eye tail, eye inner corner and pupil center, for example. 
     The face direction vector is calculated in the following sequence, for example. First, preliminarily acquired three-dimensional coordinates of a driver&#39;s facial part group are converted by rotation and translation. Then, the converted three-dimensional coordinates are projected to the target image used in the pupil detection. Then, a rotation-translation parameter which matches the facial part group detected in step S 203  in the highest degree is calculated. In this case, when the three-dimensional coordinates of the driver&#39;s facial part group is acquired preliminarily, a combination of a vector expressing a direction of the driver&#39;s face and a vector rotated by the determined rotation parameter is the face direction vector. 
     Further, the line-of-sight direction vector is calculated in the following sequence, for example. First, when the face is directed in a predetermined direction, the driver&#39;s facial part group and three-dimensional coordinates of the pupil center when the driver sees the same direction as the face direction are stored preliminarily. Detection of the pupil center is performed by obtaining a centroid of pixels having a brightness not higher than a predetermined brightness in the eye area, for example. Next, a position apart from the three-dimensional coordinates of the detected pupil in a direction opposite to the line-of-sight direction by a predetermined distance is calculated as an eye ball center position. In this case, while the above described predetermined distance is set appropriately to be approximately 12 mm which is an eye ball radius of a typical adult human, the distance is not limited to the above described value and an optional value may be used. Next, the three-dimensional coordinates of the eye ball center at the time of detection is calculated by the use of the face rotation-translation parameter acquired in the face direction vector calculation. Next, the pupil is assumed to exist on a sphere which has the center at the eye ball center and a radius of the above described predetermined distance, and it is searched for at what position on the above described sphere the detected pupil center exists. Lastly, a vector connecting the eye ball center and the point searched for on the sphere is calculated as the line-of-sight direction. 
     &lt;Pupil Actual Size Calculation Processing&gt; 
     In step S 211 , pupil actual size calculation section  109  calculates a pupil actual size from the eye area actual size value in the normalized eye area image acquired from eye area image normalization section  107  and the pupil diameter acquired from pupil detection section  108 . 
     Actual size D rt  of the pupil is calculated by equation 3 when a scale-up/scale-down factor of the normalized eye area image is denoted by n and a pupil diameter on the normalized eye area image of the detected pupil is denoted by D n . This actual size pupil diameter is retained in actual size pupil diameter storage section  104 . 
     
       
         
           
             
               
                 
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     &lt;End Determination Processing&gt; 
     In step S 212 , end determination is performed. The end determination may be performed by manual input of an end instruction or may be performed by pupil detection apparatus  100  with any external signal as a trigger. 
     When the processing is determined to be ended in step S 212 , the processing of  FIG. 3  ends. 
     As described above, according to the present embodiment, in pupil detection apparatus  100 , necessary resolution estimation section  105  calculates the resolution target value on the basis of the actual scale prediction value calculated by pupil state prediction section  103 . Then, eye area image normalization section  107  calculates the scale-up/scale-down factor on the basis of the resolution target value calculated by necessary resolution estimation section  105  and the eye area actual scale value acquired by eye area actual size calculation section  102 , and normalizes the eye area image on the basis of the calculated scale-up/scale-down factor. Then, pupil detection section  108  detects the pupil image from the eye area image normalized by eye area image normalization section  107 . 
     Thereby, it is possible to perform the pupil detection using the normalized image scaled-up/scaled-down from the eye area image by the use of the scale-up/scale-down factor which is calculated on the basis of the actual scale prediction value of the pupil diameter and the eye area actual scale value and reflects actual conditions, and therefore it is possible to improve the pupil detection accuracy even when an image to be detected has a low resolution. 
     Further, eye area image normalization section  107  calculates the number of pixels per unit length on the basis of the eye area actual scale value and the number of pixels used in the eye area image, and calculates the scale-up/scale-down factor by obtaining a ratio of the calculated number of pixels per unit length and the resolution target value. 
     Note that, in the above explanation, assuming that the target value of the resolution is an ideal resolution, a value corresponding to the current resolution is explained as the eye area actual scale value. However, the present invention is not limited to this case, and there may be used an actual scale value in an area which is a peripheral area of the pupil and has a resolution not so much different from the resolution of the pupil image on the image. 
     Embodiment 2 
     In Embodiment 2, the eye area actual scale value is obtained by a distance sensor. 
       FIG. 6  is a block diagram showing a configuration of pupil detection apparatus  500  according to Embodiment 2 of the present invention. In  FIG. 6 , pupil detection apparatus  500  includes eye area actual size calculation section  501 . 
     Eye area actual size calculation section  501  includes a distance measuring sensor and detects the eye area actual scale value directly using the distance measuring sensor. The distance measuring sensor is a laser range sensor or a TOF (Time-Of-Flight) sensor, or the like, for example. 
     The detected eye area actual scale value is output to eye area image normalization section  107 . Note that, as in Embodiment 1, the value corresponding to a current resolution is not limited to the eye area actual scale value but may be an actual scale value of a region which is a peripheral area of the pupil and has a resolution not so much different from the resolution of the pupil image on the image. 
     As described above, according to the present embodiment, in pupil detection apparatus  500 , eye area actual size calculation section  501  includes the distance measuring sensor, and eye area image normalization section  107  calculates a scale-up/scale-down factor on the basis of a calculated resolution target value and an eye area actual scale value measured by the distance measuring sensor and normalizes the eye area image on the basis of the calculated scale-up/scale-down factor, and pupil detection section  108  detects a pupil image from the normalized eye area image. 
     Thereby, it is possible to detect the eye area actual scale value without using an image, and therefore it is possible to acquire a more accurate eye area actual scale value even when an image to be detected has a low resolution. As a result, it is possible to calculate the scale-up/scale-down factor on the basis of the more accurate eye area actual scale value and therefore it is possible to further improve the pupil detection accuracy. 
     Embodiment 3 
     In Embodiment 3, the calculation method for the actual scale prediction value of the pupil diameter is switched depending on an equilibrium state or a non-equilibrium state of illuminance. 
       FIG. 7  is a block diagram showing a configuration of pupil detection apparatus  600  according to Embodiment 3 of the present invention. In  FIG. 7 , pupil detection apparatus  600  includes illuminance sensor  601  and pupil state prediction section  602 . 
     Illuminance sensor  601  measures illuminance in a peripheral of pupil detection apparatus  600  and an imaging target at a predetermined period, and outputs the measured illuminance sequentially to pupil state prediction section  602 . 
     Pupil state prediction section  602  determines whether the illuminance is in an equilibrium state or non-equilibrium state, on the basis of a history of the illuminance measured in illuminance sensor  601 , and switches the calculation method for the actual scale prediction value of the pupil diameter on the basis of the determination result. 
     Specifically, when determining that the illuminance is in the equilibrium state, pupil state prediction section  602  calculates the actual scale prediction value of the pupil diameter on the basis of at least two pupil diameters which were detected in the past in pupil detection section  108 . That is, pupil state prediction section  602 , when determining that the illuminance is in the equilibrium state, calculates the actual scale prediction value of the pupil diameter using the above described equation 1. 
     On the other hand, pupil state prediction section  602 , when determining that the illuminance is in the non-equilibrium state, calculates the actual scale prediction value of the pupil diameter on the basis of a pupil diameter and a miosis rate which were detected in the past in pupil detection section  108 . That is, pupil state prediction section  602 , when determining that the illuminance is in the non-equilibrium state, calculates the actual scale prediction value of the pupil diameter using the above described equation 2. 
     In this manner, according to the present embodiment, pupil state prediction section  602  determines whether the illuminance is in a equilibrium state or a non-equilibrium state on the basis of the history of the illuminance measurement value, and switches the calculation method for the actual scale prediction value of the pupil diameter on the basis of the determination result. 
     Thereby, it is possible to calculate the actual scale prediction value of the pupil diameter by reflecting a photographing environment, and therefore it is possible to acquire a more accurate resolution target value even when an image to be detected has a low resolution. As a result, it is possible to calculate the scale-up/scale-down factor on the basis of the more accurate resolution target value, and therefore it is possible to further improve the pupil detection accuracy. 
     Although the above each embodiment has been explained using a case where the claimed invention is implemented with hardware, as an example, the claimed invention can be implemented with software. 
     Furthermore, each function block employed in the explanation of the above each embodiment may typically be implemented as an LSI constituted by an integrated circuit. These function blocks may be individual chips or partially or totally contained on a single chip. The term “LSI” is adopted herein but this may also be referred to as “IC,” “system LSI,” “super LSI,” or “ultra LSI,” depending on the differing extents of integration. 
     The method of implementing integrated circuit is not limited to LSI, and implementation by means of dedicated circuitry or a general-purpose processor may also be possible. After LSI manufacture, utilization of a field programmable gate array (FPGA) or a reconfigurable processor where connections and settings of circuit cells in an LSI can be reconfigured is also possible. 
     If a new integrated circuit implementation technology replacing LSI is introduced because of advancement in semiconductor technology or a different technology derived therefrom, the function blocks may of course be integrated using that technology. For example, application of biotechnology is possible. 
     The pupil detection apparatus explained in each of the above described embodiments is effectively applied to an information terminal such as a personal computer, OA equipment, and a mobile phone, and an information provision apparatus mounted on a transportation means such as a car, an airplane, a ship, and an electric train. Further, the pupil detection apparatus can be also applied to monitoring equipment, an alarming apparatus, a robot, an image-sound reproduction apparatus, and the like. 
     The disclosure of Japanese Patent Application No. 2010-213780, filed on Sep. 24, 2010, including the specification, drawings and abstract, is incorporated herein by reference in its entirety. 
     INDUSTRIAL APPLICABILITY 
     The pupil detection apparatus and the pupil detection method of the present invention can improve a pupil detection accuracy even when an image to be detected has a low resolution. 
     REFERENCE SIGNS LIST 
     
         
           100 ,  500 ,  600  Pupil detection apparatus 
           101  Eye area image acquisition section 
           102 ,  501  Eye area actual size calculation section 
           103 ,  602  Pupil state prediction section 
           104  Actual size pupil diameter storage section 
           105  Necessary resolution estimation section 
           106  Table storage section 
           107  Eye area image normalization section 
           108  Pupil detection section 
           109  Pupil actual size calculation section 
           111  Image input section 
           112  Eye area detection section 
           121  Face detection section 
           122  Facial part detection section 
           123  Eye area determination section 
           601  Illuminance sensor