Patent Publication Number: US-2023147088-A1

Title: Detection apparatus

Description:
TECHNICAL FIELD 
     The present invention relates to a detection apparatus, a detection method, and a recording medium. 
     BACKGROUND ART 
     An authentication technique such as face authentication, which is detecting a face region and performing authentication based on a feature value of the detected face region, is known. 
     For example, Patent Document 1 describes one of the techniques used to detect a face region. Patent Document 1 describes an image pickup device (imaging device) that includes a detection determination means, a correction means, a calculation means, and a cancel determination means. According to Patent Document 1, the detection determination means determines whether or not a subject region can be detected based on a plurality of types of classifiers. The correction means performs a correction process on image data when it is determined that a subject region cannot be detected. The cancel determination means compares the results calculated by the calculation means that calculates the degrees of similarity between the image data before and after the correction and the classifiers, and determines whether or not to cancel the correction process based on the results of the comparison.
     Patent Document 1: Japanese Unexamined Patent Application Publication No. JP-A 2013-198013   

     As described in Patent Document 1, there is a method of correcting image data when a region such as a face region cannot be detected by a detection means. However, in a case where a target is caught by a camera for a short time, there is a possibility that even if correction of the image data, for example, by adjustment of the parameter of the camera acquiring image data is intended, the target is out of the angle of view during the adjustment. As a result, failure to detect a face region may occur. 
     Thus, there has been a problem that it is difficult to inhibit failure to detect a face region. 
     SUMMARY 
     Accordingly, an object of the present invention is to provide a detection apparatus, a detection method, and a recording medium which solve the problem that it is difficult to inhibit failure to detect a face region. 
     In order to achieve the object, a detection method as an aspect of the present disclosure is a detection method executed by a detection apparatus. The detection method includes: performing detection of a face region based on image data acquired by a predetermined imaging device; and changing setting for performing a face region detection process with image data acquired by another imaging device, based on a result of the detection. 
     Further, a detection apparatus as another aspect of the present disclosure includes: a detection unit configured to perform detection of a face region based on image data acquired by a predetermined imaging device; and a setting change unit configured to change setting for performing a face region detection process with image data acquired by another imaging device, based on a result of the detection by the detection unit. 
     Further, a recording medium as another aspect of the present disclosure is a non-transitory computer-readable recording medium having a program recorded thereon. The program includes instructions for causing a detection apparatus to realize: a detection unit configured to perform detection of a face region based on image data acquired by a predetermined imaging device; and a setting change unit configured to change setting for performing a face region detection process with image data acquired by another imaging device, based on a result of the detection by the detection unit. 
     The configurations as described above make it possible to provide a detection apparatus, a detection method, and a recording medium which can inhibit failure to detect a face region. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a view showing an example of a configuration of a face authentication system in a first example embodiment of the present disclosure; 
         FIG.  2    is a block diagram showing an example of a configuration of a face authentication apparatus shown in  FIG.  1   ; 
         FIG.  3    is a view showing an example of image information shown in  FIG.  2   ; 
         FIG.  4    is a view showing an example of posture information shown in  FIG.  2   ; 
         FIG.  5    is a view for describing processing by a face region estimation unit; 
         FIG.  6    is a block diagram showing an example of a configuration of a camera shown in  FIG.  1   ; 
         FIG.  7    is a flowchart showing an example of an operation of the face authentication apparatus in the first example embodiment of the present disclosure; 
         FIG.  8    is a view showing an example of a configuration of a face authentication system in a second example embodiment of the present disclosure; 
         FIG.  9    is a block diagram showing an example of a configuration of a face authentication apparatus shown in  FIG.  8   ; 
         FIG.  10    is a view for showing an example of processing by a move destination estimation unit shown in  FIG.  9   ; 
         FIG.  11    is a flowchart showing an example of an operation of the face authentication apparatus in the second example embodiment of the present disclosure; 
         FIG.  12    is a block diagram showing another example of the configuration of the face authentication apparatus in the second example embodiment of the present disclosure; 
         FIG.  13    is a view showing an example of a configuration of a face authentication system in a third example embodiment of the present disclosure; 
         FIG.  14    is a block diagram showing an example of a configuration of a face authentication apparatus shown in  FIG.  13   ; 
         FIG.  15    is a view showing an example of authentication-related information shown in  FIG.  14   ; 
         FIG.  16    is a block diagram showing an example of a configuration of a camera shown in  FIG.  13   ; 
         FIG.  17    is a flowchart showing an example of an operation of the face authentication apparatus in the third example embodiment of the present disclosure; 
         FIG.  18    is a view showing an example of a hardware configuration of a detection apparatus in a fourth example embodiment of the present disclosure; and 
         FIG.  19    is a block diagram showing an example of a configuration of the detection apparatus shown in  FIG.  18   . 
     
    
    
     EXAMPLE EMBODIMENTS 
     First Example Embodiment 
     A first example embodiment of the present disclosure will be described with reference to  FIGS.  1  to  7   .  FIG.  1    is a view showing an example of a configuration of a face authentication system  100 .  FIG.  2    is a block diagram showing an example of a configuration of a face authentication apparatus  200 .  FIG.  3    is a view showing an example of image information  234 .  FIG.  4    is a view showing an example of posture information  235 .  FIG.  5    is a view for describing processing by a face region estimation unit  244 .  FIG.  6    is a block diagram showing an example of a configuration of a camera  300 .  FIG.  7    is a flowchart showing an example of an operation of the face authentication apparatus  200 . 
     In the first example embodiment of the present disclosure, the face authentication system  100  that detects a face region and performs face authentication will be described. As will be described later, in a case where the face authentication system  100  cannot detect the face region of an authentication target person based on image data acquired by a camera  300 - 1 , the face authentication system  100  adjusts a parameter of an estimated region and the like based on the result of posture detection, and also reconfirms whether a face region is detected in the estimated region. In a case where a face region is not detected by the reconfirmation, the face authentication system  100  instructs a camera  300 - 2  that is a move destination camera to perform parameter adjustment, and adjusts a face detection threshold value used in detection of a face region. Then, the face authentication system  100  performs detection of a face region using the adjusted face detection threshold value based on image data acquired by the camera  300 - 2  after parameter adjustment. Thus, in a case where the face authentication system  100  cannot detect a face region based on image data acquired by the camera  300 - 1  that is a predetermined imaging device, the face authentication system  100  changes setting for performing a face region detection process based on image data acquired by the camera  300 - 2  that is another imaging device. The setting to be changed includes, for example, at least one of the parameter used when the camera  300  acquires image data and the face detection threshold value. 
       FIG.  1    shows an example of a configuration of the whole face authentication system  100 . Referring to  FIG.  1   , the face authentication system  100  includes, for example, the face authentication apparatus  200  and two cameras  300  (the camera  300 - 1  and the camera  300 - 2 , which will be described as the camera  300  when not particularly discriminated). As shown in  FIG.  1   , the face authentication apparatus  200  and the camera  300 - 1  are connected so as to be able to communicate with each other. Moreover, the face authentication apparatus  200  and the camera  300 - 2  are connected so as to be able to communicate with each other. 
     The face authentication system  100  is deployed in, for example, a shopping mall, an airport and a shopping street, and performs face authentication to search for a suspicious person, a lost child, and the like. A place to deploy the face authentication system  100  and a purpose that the face authentication system  100  performs face authentication may be other than those illustrated above. 
     The face authentication apparatus  200  is an information processing apparatus that performs face authentication based on image data acquired by the camera  300 - 1  and the camera  300 - 2 . For example, in a case where the face authentication apparatus  200  cannot detect a face region based on image data acquired by the camera  300 - 1 , the face authentication apparatus  200  performs detection of a face region based on image data acquired by the camera  300 - 2 .  FIG.  2    shows an example of a configuration of the face authentication apparatus  200 . Referring to  FIG.  2   , the face authentication apparatus  200  includes, as major components, a screen display unit  210 , a communication I/F unit  220 , a storage unit  230 , and an operation processing unit  240 , for example. 
     The screen display unit  210  includes a screen display deice such as an LCD (Liquid Crystal Display). The screen display unit  210  displays, on a screen, information stored in the storage unit  230  such as authentication result information  236  in accordance with an instruction from the operation processing unit  240 . 
     The communication I/F unit  220  includes a data communication circuit. The communication I/F unit  220  performs data communication with the camera  300  and an external device connected via a communication line. 
     The storage unit  230  is a storage device such as a hard disk and a memory. The storage unit  230  stores therein processing information necessary for various processing by the operation processing unit  240  and a program  237 . The program  237  is loaded to and executed by the operation processing unit  240  to realize various processing units. The program  237  is loaded in advance from an external device or a recording medium via a data input/output function such as the communication I/F unit  220 , and is stored in the storage unit  230 . Major information stored in the storage unit  230  includes, for example, information for detection  231 , a trained model  232 , feature value information  233 , the image information  234 , posture information  235 , and the authentication result information  236 . 
     The information for detection  231  is information used when a face region detection unit  242  performs detection of a face region. As will be described later, the face region detection unit  242  may perform face detection by a generally-used face detection technique. Therefore, information included by the information for detection  231  may also be information corresponding to a method by which the face region detection unit  242  performs face detection. For example, the information for detection  231  may be a model trained based on luminance gradient information. The information for detection  231  is, for example, acquired in advance from an external device via the communication I/F unit  220  and stored in the storage unit  230 . 
     The trained model  232  is a model having been trained, used when a posture detection unit  243  performs posture detection. The trained model  232  is, for example, generated in advance by learning using training data such as image data containing skeletal coordinates in an external device or the like, and is acquired from the external device or the like via the communication I/F unit  220  or the like and stored in the storage unit  230 . 
     The feature value information  233  includes information indicating a face feature value used when a face authentication unit  246  performs face authentication. In the feature value information  233 , for example, identification information for identifying a person and information indicating a face feature value are associated with each other. The feature value information  233  is, for example, acquired in advance from an external device or the like via the communication I/F unit  220  or the like, and is stored in the storage unit  230 . 
     The image information  234  includes image data acquired by the camera  300 . In the image information  234 , for example, the image data and information indicating time and date of acquisition of the image data by the camera  300  are associated with each other. 
       FIG.  3    shows an example of the image information  234 . As shown in  FIG.  3   , the image information  234  includes image data acquired from the camera  300 - 1  and image data acquired from the camera  300 - 2 . 
     The posture information  235  includes information indicating a person&#39;s posture detected by the posture detection unit  243 . For example, the posture information  235  includes information indicating the coordinates of each site of a person.  FIG.  4    shows an example of the posture information  235 . Referring to  FIG.  4   , in the posture information  235 , identification information and site coordinates are associated with each other. 
     Sites included in the site coordinates correspond to those of the trained model  232 . For example,  FIG.  4    illustrates the upper part of the backbone, the right shoulder, the left shoulder, . . . . The site coordinates can include, for example, approximately 30 sites (may be other than those illustrated). The sites included in the site coordinates may be other than those illustrated in  FIG.  4    and others. 
     The authentication result information  236  includes information indicating the result of authentication by the face authentication unit  246 . The details of processing by the face authentication unit  246  will be described later. 
     The operation processing unit  240  has a microprocessor such as an MPU and a peripheral circuit thereof, and loads the program  237  from the storage unit  230  and executes the program  237  to make the abovementioned hardware and the program  237  cooperate and realize various processing units. The major processing units realized by the operation processing unit  240  are, for example, an image acquisition unit  241 , the face region detection unit  242 , the posture detection unit  243 , the face region estimation unit  244 , a parameter adjustment unit  245 , the face authentication unit  246 , and an output unit  247 . 
     The image acquisition unit  241  acquires image data acquired by the camera  300  from the camera  300  via the communication IN unit  220 . Then, the image acquisition unit  241  associates the acquired image data with, for example, the time and date of acquisition of the image data, and stores as the image information  234  into the storage unit  230 . 
     In this example embodiment, the image acquisition unit  241  acquires image data from the camera  300 - 1 , and also acquires image data from the camera  300 - 2 . The image acquisition unit  241  may acquire image data from the camera  300 - 1  and the camera  300 - 2  at all times or, for example, may not acquire image data from the camera  300 - 2  until a predetermined condition is satisfied. For example, in a case where the face authentication apparatus  200  cannot detect a face region based on image data acquired by the camera  300 - 1 , the face authentication apparatus  200  perform detection of a face region based on image data acquired by the camera  300 - 2 . Therefore, the image acquisition unit  241  may be configured to, in a case where a face region cannot be detected based on image data acquired by the camera  300 - 1 , acquire image data from the camera  300 - 2 . 
     The face region detection unit  242  detects a face region of a person based on image data included by the image information  234 . As described above, the face region detection unit  242  can detect a face region by a known technique. For example, the face region detection unit  242  performs detection of a face region using the information for detection  231  and a face detection threshold value. In other words, the face region detection unit  242  can detect a region where, for example, the degree of similarity to the information for detection  231  is equal to or more than the face detection threshold value, as a face region. 
     In this example embodiment, first, the face region detection unit  242  performs detection of a face region based on image data acquired from the camera  300 - 1  among image data included by the image information  234 . 
     Further, in a case where a face region cannot be detected based on the image data acquired from the camera  300 - 1 , the parameter adjustment unit  245  adjust a parameter of a region estimated based on the result of posture detection. After the abovementioned parameter adjustment, the face region detection unit  242  can confirm whether or not a face region exists in a region estimated by the face region estimation unit  244  based on the result of posture detection. In other words, the face region detection unit  242  can perform detection of a face region in a region estimated by the face region estimation unit  244  in a state that the parameter adjustment unit  245  has adjusted a parameter of a region estimated by the face region estimation unit  244 . 
     Further, in a case where a face region is not detected even by reconfirmation (for example, in a case where a face region cannot be detected for a predetermined time period), the parameter adjustment unit  245  instructs the camera  300 - 2  to adjust a parameter, and the face detection threshold value is adjusted. For example, the parameter adjustment unit  245  lowers the face detection threshold value. The face region detection unit  242  can detect a face region using the adjusted face detection threshold value based on image data acquired by the camera  300 - 2  after the parameter adjustment. By performing face detection in a state that the face detection threshold value is lowered, a probability that face detection can be performed increases. 
     For example, as described above, the face region detection unit  242  can perform detection of a face region by various methods, such as detection of a face region based on image data acquired from the camera  300 - 1 , detection of a face region based on image data acquired from the camera  300 - 1  and the camera  300 - 2  after parameter adjustment. 
     The posture detection unit  243  detects the posture of an authentication target person in image data by recognizing the skeleton of the person by using the trained model  232 . For example, as shown in  FIG.  4   , the posture detection unit  243  recognizes sites such as the upper part of the backbone, the right shoulder, and the left shoulder. Moreover, the posture detection unit  243  calculates the coordinates in screen data of each of the recognized sites. Then, the posture detection unit  243  associates the recognition and calculation results with identification information, and stores as the posture information  235  into the storage unit  230 . 
     The sites recognized by the posture detection unit  243  correspond to those of the trained model  232  (training data used for training the trained model  232 ). Therefore, the posture detection unit  243  may recognize a site other than the sites illustrated above in accordance with the trained model  232 . 
     The face region estimation unit  244  estimates a region where a face region is estimated to exist based on the result of detection by the posture detection unit  243 . For example, the face region estimation unit  244  estimates the region, for example, in a case where the face region detection unit  242  cannot detect a face region while the posture detection unit  243  detects a posture. The face region estimation unit  244  may estimate the region at a timing other than that illustrated above. 
       FIG.  5    is a view for describing an example of estimation by the face region estimation unit  244 . As shown in  FIG.  5   , it can be estimated that a face region is located in the vicinity of the shoulders, neck and the like on the opposite side to a side where the hips, legs and others are located when viewed from a site such as the shoulders. Then, the face region estimation unit  244  can estimate a region where a face region is thought to exist by confirming the coordinates of each site with reference to the posture information  235 . 
     The parameter adjustment unit  245  adjusts parameters used in the face authentication process, such as a parameter used when the camera  300  acquires image data and a face detection threshold value. 
     For example, in a case where the face region detection unit  242  cannot detect a face region based on image data acquired from the camera  300 - 1 , the parameter adjustment unit  245  performs parameter adjustment on a region estimated by the face region estimation unit  244 . Specifically, for example, the parameter adjustment unit  245  instructs the camera  300 - 1  to performs adjustment of parameters used when the camera  300 - 1  acquires image data on a region estimated by the face region estimation unit  244 . Consequently, the camera  300 - 1  corrects the parameters and acquires image data by using the corrected parameters. 
     The parameter adjustment unit  245  may instruct the camera  300 - 1  to perform parameter correction on the entire image data. Moreover, together with the instruction to the camera  300 - 1  described above, the parameter adjustment unit  245  may perform adjustment of parameters used when the face region detection unit  242  detects a face region, for example, lower the face detection threshold value. 
     Further, in a case where the face region detection unit  242  cannot detect a face region even by reconfirmation, the parameter adjustment unit  245  instructs the camera  300 - 2  to adjust parameters used in acquisition of image data. When the parameter adjustment unit  245  instructs the camera  300 - 2  to adjust parameters based on the result of detection of a face region based on image data acquired by the camera  300 - 1 , it is thereby possible to adjust the parameters in advance, for example, before an authentication target person is caught in image data acquired by the camera  300 - 2 . Moreover, the parameter adjustment unit  245  can adjust the parameters used when the face region detection unit  242  detects a face region, for example, lower the face detection threshold value. 
     For example, as described above, the parameter adjustment unit  245  adjusts parameters used in face authentication based on the result of detection by the face region detection unit  242 . 
     The parameters that the parameter adjustment unit  245  instructs the camera  300  to adjust include, for example, brightness, sharpness, contrast and the like, and a frame rate indicating the number of image data acquisitions per unit time. For example, in a case where it is assumed that face detection has failed because the brightness value is too high due to backlight, the parameter adjustment unit  245  instructs to lower the brightness. The parameters adjusted by the parameter adjustment unit  245  may be at least some of those illustrated above, or may be other than those illustrated above. 
     Further, the parameter adjustment unit  245  can instruct the camera  300 - 1  and the camera  300 - 2  to perform parameter adjustment and also instruct the time for performing parameter adjustment. For example, it is possible to calculate in advance a time from when an authentication target person is caught in image data acquired by the camera  300 - 1  to when the authentication target person is caught in image data acquired by the camera  300 - 2 , based on information indicating the installation positions of the camera  300 - 1  and the camera  300 - 2  and information indicating a walking speed. Then, the parameter adjustment unit  245  may instruct the camera  300 - 2  to perform parameter adjustment during a time that the authentication target person is estimated to be caught by the camera  300 - 2 . The time to instruct the camera  300 - 2  to perform parameter adjustment may be estimated in advance, for example, by using a normal walking speed, or may be calculated based on the walking speed of the person calculated based on the image data acquired by the camera  300 - 1 . 
     The face authentication unit  246  performs face authentication by using the result of detection by the face region detection unit  242 . Then, the face authentication unit  246  stores the result of the face authentication as the authentication result information  236  into the storage unit  230 . 
     For example, the face authentication unit  246  extracts feature points such as the eyes, nose and mouth of a person in the face region detected by the face region detection unit  242 , and calculates a feature value based on the extracted result. Then, for example, by confirming whether or not the degree of similarity between the calculated feature value and the face feature value included in the feature value information  233  exceeds a face comparison threshold value, the face authentication unit  246  performs matching between the calculated feature value and the feature value stored in the storage unit  230 , and performs authentication based on the result of matching. By performing face authentication in this manner, the face authentication unit  246  can identify an identification target person such as a lost child. 
     The output unit  247  outputs the authentication result information  236  indicating the result of the authentication process by the face authentication unit  246 . The output by the output unit  247  is, for example, displaying on a screen of the screen display unit  210 , or transmitting to an external device via the communication IN unit  220 . 
     The above is an example of a configuration of the face authentication apparatus  200 . 
     The camera  300  is an imaging device that acquires image data, for example, a surveillance camera.  FIG.  6    shows an example of a configuration of the camera  300 . Referring to  FIG.  6   , the camera  300  includes, for example, a transmission and reception unit  310 , a setting unit  320 , and an imaging unit  330 . 
     For example, the camera  300  includes an arithmetic logic unit such as a CPU and a storage unit. The camera  300  can realize the abovementioned processing units by execution of a program stored in the storage unit by the arithmetic logic unit. 
     The transmission and reception unit  310  transits and receives data to and from the face authentication apparatus  200  and the like. For example, the transmission and reception unit  310  transmits image data acquired by the imaging unit  330  to the face authentication apparatus  200 . Moreover, the transmission and reception unit  310  receives a parameter adjustment instruction and the like from the face authentication apparatus  200 . 
     The setting unit  320  adjusts a parameter used when the imaging unit  330  acquires image data based on a parameter adjustment instruction received from the face authentication apparatus  200 . For example, the setting unit  320  adjusts brightness, sharpness, contrast, frame rate, and the like, based on an instruction received from the face authentication apparatus  200 . The setting unit  320  can perform parameter adjustment on a designated region in accordance with an instruction. 
     The imaging unit  330  acquires image data by using a parameter set by the setting unit  320 . Image data acquired by the imaging unit  330  can be associated with time and date of acquisition of image data by the imaging unit  330 , and the like, and transmitted to the face authentication apparatus  200  via the transmission and reception unit  310 . 
     The above is an example of a configuration of the camera  300 . Subsequently, an example of an operation of the face authentication apparatus  200  will be described with reference to  FIG.  7   . 
     Referring to  FIG.  7   , the face region detection unit  242  performs detection of a face region based on image data acquired from the camera  300 - 1  among image data included by the image information  234  (step S 101 ). 
     In a case where a face region cannot be detected, for example, for a predetermined time period (step S 102 , No), the face region estimation unit  244  estimates a region where a face region is estimated to exist based on the result of detection by the posture detection unit  243  (step S 103 ). Moreover, the parameter adjustment unit  245  instructs the camera  300 - 1  to perform adjustment of a parameter used when the camera  300 - 1  acquires image data on the region estimated by the face region estimation unit  244  (step S 104 ). Then, the camera  300 - 1  corrects the parameter. 
     The face region detection unit  242  performs detection of a face region on the region estimated by the face region estimation unit  244  (step S 105 ). 
     In a case where a face region cannot be detected, for example, for a predetermined time period (step S 106 , No), the parameter adjustment unit  245  instructs the camera  300 - 2  to adjust a parameter used in acquisition of image data. Moreover, the parameter adjustment unit  245  adjusts a parameter used when the face region detection unit  242  performs detection of a face region, for example, lowers a face detection threshold value (step S 107 ). 
     The face region detection unit  242  performs detection of a face region using the adjusted face detection threshold value based on image data acquired by the camera  300 - 2  after the parameter adjustment (step S 108 ). 
     When the face region detection unit  242  detects a face region, the face authentication unit  246  performs face authentication using the result of detection by the face region detection unit  242  (step S 109 ). 
     The above is an example of the operation of the face authentication apparatus  200 . 
     Thus, the face authentication apparatus  200  includes the face region detection unit  242  and the parameter adjustment unit  245 . With such a configuration, the parameter adjustment unit  245  can instruct the camera  300 - 2  to adjust a parameter based on the result of detection of a face region based on image data acquired by the camera  300 - 1 . Moreover, the parameter adjustment unit  245  can lower a face detection threshold value in advance. As a result, the face region detection unit  242  can perform detection of a face region based on image data acquired in a state that a parameter is adjusted in advance. Consequently, it becomes possible to appropriately adjust a parameter and inhibit failure to detect a face region. 
     Further, with the above configuration, for example, it becomes possible to increase the frame rate of the camera  300 - 2  only at a timing when detection of a face region based on image data acquired by the camera  300 - 2  is required. As a result, it is possible to inhibit unnecessarily increasing data traffic, and it becomes possible to realize efficient processing. 
     Further, the face authentication apparatus  200  includes the posture detection unit  243  and the face region estimation unit  244 . With such a configuration, the face region estimation unit  244  can estimate a region where a face region is estimated to exist, based on the result of detection by the posture detection unit  243 . As a result, for example, it becomes possible to narrow down the range of parameter adjustment by the parameter adjustment unit  245  and the range of detection of a face region by the face region detection unit  242 , and it becomes possible to realize efficient parameter adjustment and face region detection. 
     In this example embodiment, the parameter adjustment unit  245  instructs the camera  300 - 2  to adjust a parameter used in acquisition of image data when the face region detection unit  242  cannot detect a face region even by reconfirmation. However, the parameter adjustment unit  245  may be configured to, when a face region cannot be detected based on image data acquired from the camera  300 - 1 , instruct the camera  300 - 2  to perform parameter correction without reconfirmation. In this case, for example, the processes from steps S 103  to S 105  described with reference to  FIG.  7    may be omitted. Moreover, in a case where the processes from steps S 103  to S 105  are not performed, the face authentication apparatus  200  may not have the posture detection unit  243  and the face region estimation unit  244 . For example, as described above, the face authentication apparatus  200  may have only part of the configuration illustrated in  FIG.  2     
     Further,  FIG.  2    illustrates a case of realizing the function as the face authentication apparatus  200  by using one information processing apparatus. However, the function as the face authentication apparatus  200  may be realized by, for example, a plurality of information processing apparatuses connected via a network. 
     Second Example Embodiment 
     Next, a second example embodiment of the present disclosure will be described with reference to  FIGS.  8  to  12   .  FIG.  8    is a view showing an example of a configuration of a face authentication system  400 .  FIG.  9    is a block diagram showing an example of a configuration of a face authentication apparatus  500 .  FIG.  10    is a view for describing an example of processing by a move destination estimation unit  548 .  FIG.  11    is a flowchart showing an example of an operation of the face authentication apparatus  500 .  FIG.  12    is a block diagram showing another example of the configuration of the face authentication apparatus  500 . 
     In the second example embodiment of the present disclosure, the face authentication system  500 , which is a modified example of the face authentication system  100  described in the first example embodiment, will be described. In the first example embodiment, the face authentication system  100  including two cameras  300 , that is, the camera  300 - 1  and the camera  300 - 2  has been described. In this example embodiment, the face authentication system  400  including three or more cameras  300  will be described. As will be described later, when the face authentication system  400  cannot detect a face region based image data acquired by the camera  300 - 1 , the face authentication system  400  estimates a camera to be a move destination based on the result of posture detection. Then, the face authentication system  400  instructs the estimated camera  300  to perform parameter adjustment. 
       FIG.  8    shows an example of a configuration of the whole face authentication system  400 . Referring to  FIG.  8   , the face authentication system  400  includes the face authentication apparatus  500  and three cameras  300  (camera  300 - 1 , camera  300 - 2 , camera  300 - 3 ). As shown in  FIG.  8   , the face authentication apparatus  500  and the camera  300 - 1  are connected so as to be able to communicate with each other. The face authentication apparatus  500  and the camera  300 - 2  are connected so as to be able to communicate with each other. The face authentication apparatus  500  and the camera  300 - 3  are connected so as to be able to communicate with each other. 
       FIG.  8    illustrates a case where the face authentication system  400  includes three cameras  300 . However, the number of the cameras  300  included by the face authentication system  400  is not limited to three. The face authentication system  400  may include four or more cameras  300 . 
     The face authentication apparatus  500 , as well as the face authentication apparatus  200  described in the first example embodiment, is an information processing apparatus that performs face authentication.  FIG.  9    shows an example of a configuration of the face authentication apparatus  500 . Referring to  FIG.  9   , the face authentication apparatus  500  includes, as major components, a screen display unit  210 , a communication I/F unit  220 , a storage unit  230 , and an operation processing unit  540 , for example. Below, a configuration which is characteristic of this example embodiment will be described. 
     The operation processing unit  540  includes a microprocessor such as an MPU and a peripheral circuit thereof, and retrieves the program  237  from the storage unit  230  and executes the program  237  to make the abovementioned hardware and the program  237  cooperate and realize various processing units. Major processing units realized by the operation processing unit  540  are, for example, the image acquisition unit  241 , the face region detection unit  242 , the posturer detection unit  243 , the face region estimation unit  244 , a parameter adjustment unit  545 , the face authentication unit  246 , an output unit  546 , and a move destination estimation unit  548 . 
     The move destination estimation unit  548  estimates the camera  300  located in the move destination of a person whose face region cannot be detected, based on the result of detection by the posture detection unit  243 . For example, in a case where the face region detection unit  242  cannot detect a face region even by reconfirmation, the move destination estimation unit  548  refers to the posture information  235 , and acquires information indicating the installation position of the camera  300 . Then, the move destination estimation unit  548  estimates the camera  300  located in the move destination of the person based on the posture information  235  and the information indicating the installation position of the camera  300 . 
       FIG.  10    is a view for describing an example of estimation by the move destination estimation unit  548 . As shown in  FIG.  10   , the body of a person is generally oriented in the moving direction. Therefore, it can be estimated that a direction in which the body of a person to be determined based on the posture information  235  faces is the moving direction of the person. The move destination estimation unit  548  estimates that the camera  300  located ahead of the estimated movement direction of the person is the camera  300  located at the move destination of the person, based on the posture information  235  and the information indicating the installation position of the camera  300 . 
     The move destination estimation unit  548  may be configured to extract the movement locus of a person based on image data of a plurality of frames and estimate the camera  300  whether the camera  300  is located at the move destination based on the extracted movement locus. The move destination estimation unit  548  may perform estimation by combining estimation based on the result of detection by the posture detection unit  243  and estimation based on the movement locus, for example. 
     The parameter adjustment unit  545  adjusts parameters used in the face authentication process, such as a parameter used when the camera  300  acquires image data and a face detection threshold value. 
     For example, when the face region detection unit  242  cannot detect a face region based on image data acquired from the camera  300 - 1 , the parameter adjustment unit  545  performs parameter adjustment on a region estimated by the face region estimation unit  244 . Specifically, for example, the parameter adjustment unit  245  instructs the camera  300 - 1  to perform adjustment of a parameter used when the camera  300 - 1  acquires image data on a region estimated by the face region estimation unit  244 . Then, the camera  300 - 1  corrects the parameter and acquires image data using the corrected parameter. 
     Further, in a case where the face region detection unit  242  cannot detect a face region even by reconfirmation, the parameter adjustment unit  545  instructs the camera  300  estimated by the move destination estimation unit  548  to adjust a parameter used in acquisition of image data. Moreover, the parameter adjustment unit  545  can adjust a parameter used when the face region detection unit  242  detects a face region, for example, lower the face detection threshold value. 
     For example, as described above, when adjusting the parameter of the move destination camera  300 , the parameter adjustment unit  545  instructs the camera  300  estimated by the move destination estimation unit  548  to perform parameter adjustment. 
     The output unit  547  outputs the authentication result information  236  indicating the result of the authentication process by the face authentication unit  246 . The output by the output unit  547  is, for example, displaying on a screen of the screen display unit  210 , or transmitting to an external device via the communication I/F unit  220 . 
     Further, the output unit  547  can output information of an identification target person identified by authentication by the face authentication unit  246 , and the like, and also output information indicating a moving direction of the person estimated by the move destination estimation unit  548 , and the like. By outputting the information indicating the moving direction together with the information of the identification target person having been identified, a person who receives the output by the output unit  547  can know the moving direction of the identification target, and can find the identification target person more rapidly. 
     The above is a description of the configuration that is characteristic of this example embodiment in the configuration of the face authentication apparatus  500 . Subsequently, an example of an operation of the face authentication apparatus  500  will be described with reference to  FIG.  11   . Hereinafter, an operation that is characteristic of this example embodiment in the operation of the face authentication apparatus  500  will be described. 
     The processes up to step S 105  are the same as in the operation of the face authentication apparatus  200  described in the first example embodiment. In a case where a face region cannot be detected, for example, for a predetermined time period after the process at step S 105  (step S 106 , No), the move destination estimation unit  548  estimates the camera  300  located at the move destination of the person (step S 201 ). 
     The parameter adjustment unit  545  instructs the camera  300  estimated by the move destination estimation unit  548  to adjust a parameter used in acquisition of image data. Moreover, the parameter adjustment unit  245  adjusts a parameter used when the face region detection unit  242  performs detection of a face region, for example, lowers a face detection threshold value (step S 107 ). The subsequent processes are the same as in the operation of the face authentication apparatus  200  described in the first example embodiment. 
     The above is an operation that is characteristic of this example embodiment in the example of the operation of the face authentication apparatus  500 . 
     Thus, the face authentication apparatus  500  includes the move destination estimation unit  548  and the parameter adjustment unit  245 . With such a configuration, the parameter adjustment unit  245  can instruct the camera  300  estimated by the move destination estimation unit  548  to adjust a parameter used in acquisition of image data. As a result, it becomes possible to adjust only the parameter of the required camera  300  in advance, and it becomes possible to more exactly adjust even when three or more cameras  300  are provided. Moreover, since it is possible to inhibit increase of the frame rate of the camera  300  that is not the move destination, it is possible to inhibit a situation in which data traffic is unnecessarily increased, for example. 
     The move destination estimation unit  548  may use information for move destination estimation  238  stored in the storage unit  230  as shown in  FIG.  12    when estimating the camera  300  located at the move destination. The information for move destination estimation  238  can include, other than information indicating the position of the camera  300 , for example, information indicating the movement tendency of persons for each time of day such that many people heads in this direction in the morning time, information indicating the movement tendency for each person&#39;s attribute such as clothes, belongings, gender and age. The information for move destination estimation  238  may include information other than the information used in estimation of the move destination illustrated above. 
     Further, the face authentication system  400  and the face authentication apparatus  500  can be modified in various manners as described in the first example embodiment. 
     Third Example Embodiment 
     Next, a third example embodiment of the present disclosure will be described with reference to  FIGS.  13  to  17   .  FIG.  13    is a view showing an example of a configuration of a face authentication system  600 .  FIG.  14    is a block diagram showing an example of a configuration of a face authentication apparatus  700 .  FIG.  15    is a view showing an example of authentication-related information  732 .  FIG.  16    is a block diagram showing an example of a configuration of a camera  800 .  FIG.  17    is a flowchart showing an example of an operation of the face authentication apparatus  700 . 
     In the third example embodiment of the present disclosure, the face authentication system  600  that detects a face region and performs face authentication will be described. As will be described later, the face authentication system  600  manages person-related information such as the color of clothes and belongings of a person whose face has been authenticated. Moreover, when it is determined that a person having an unauthenticated feature is caught in image data based on the person-related information, the face authentication system  600  instructs the camera  800  to magnify the face of the person by optical zoom, digital zoom, or the like, on the person. 
       FIG.  13    shows an example of a configuration of the whole face authentication system  600 . Referring to  FIG.  13   , the face authentication system  600  includes the face authentication apparatus  700  and the camera  800 . As shown in  FIG.  13   , the face authentication apparatus  700  and the camera  800  are connected so as to be able to communicate with each other. 
       FIG.  13    illustrates a case where the face authentication system  600  includes one camera  800 . However, the number of the cameras  800  included by the face authentication system  600  is not limited to one. The face authentication system  600  may include two or more cameras  800 . Moreover, in a case where the face authentication system  600  includes two or more cameras  800 , the face authentication apparatus  700  may have a function as the face authentication apparatus  200  described in the first example embodiment or the face authentication apparatus  500  described in the second example embodiment. 
     The face authentication apparatus  700  is an information processing apparatus that performs face authentication based on image data acquired by the camera  800 . For example, in a case where the face authentication apparatus  700  determines that a person having an unauthenticated feature is caught in image data based on the person-related information managed thereby, the face authentication apparatus  700  instructs the camera  800  to magnify the person and the face of the person by optical zoom, digital zoom, or the like, on the person. Then, the face authentication apparatus  700  performs detection of a face region and performs face authentication based on the image data in which the person is magnified.  FIG.  14    shows an example of a configuration of the face authentication apparatus  700 . Referring to  FIG.  14   , the face authentication apparatus  700  includes, as major components, a screen display unit  710 , a communication I/F unit  720 , a storage unit  730 , and an operation processing unit  740 , for example. 
     The configurations of the screen display unit  710  and the communication I/F unit  720  may be the same as those of the screen display unit  210  and the communication I/F unit  220  described in the first and second example embodiments. Therefore, a description thereof will be omitted. 
     The storage unit  730  is a storage device such as a hard disk and a memory. The storage unit  730  stores therein processing information necessary for various processing in the operation processing unit  740  and a program  734 . The program  734  is loaded to and executed by the operation processing unit  740  to realize various processing units. The program  734  is retrieved in advance from an external device or a recording medium via a data input/output function such as the communication I/F unit  720  and is stored in the storage unit  730 . Major information stored in the storage unit  730  are, for example, information for detection  731 , authentication-related information  732 , and image information  733 . 
     The information for detection  731  may be the same as the information for detection  231  described in the first and second example embodiments. Therefore, a description thereof will be omitted. 
     The authentication-related information  732  includes information indicating a face feature value used when the face authentication unit  745  performs face authentication. Moreover, the authentication-related information  732  includes information indicating whether or not authentication has been performed, person-related information such as the color of clothes and belongings of a person, and the like. 
       FIG.  15    shows an example of the authentication-related information  732 . Referring to  FIG.  15   , in the authentication-related information  732 , for example, information indicating the feature value of a person, identification information such as name, the presence or absence of detection indicating whether or not authentication has been performed, the color of clothes, and belongings are associated with each other. The authentication-related information  732  may include person-related information other than the color of clothes and the belongings. 
     The image information  733  includes image data acquired by the camera  800 . In the image information  733 , for example, the image data, information indicating time and date of acquisition of the image data by the camera  800 , and the like, are associated with each other. As described above, the camera  800  may acquire image data in which a person or a face is magnified in accordance with an instruction from the face authentication apparatus  700 . Therefore, the image information  733  includes image data in which a person or a face is magnified. 
     The operation processing unit  740  includes a microprocessor such as an MPU and a peripheral circuit, and retrieves the program  734  from the storage unit  730  and executes the program  734  to make the above hardware and the programs cooperate with each other and realize various processing units. Major processing units realized by the operation processing unit  740  are, for example, an image acquisition unit  741 , a feature detection unit  742 , a magnification instruction unit  743 , a face region detection unit  744 , and a face authentication unit  74 . 
     The image acquisition unit  741  acquires image data acquired by the camera  800  from the camera  800  via the communication I/F unit  720 . Then, the image acquisition unit  741  associates the acquired image data with, for example, time and date of acquisition of the image data and stores as the image information  733  into the storage unit  730 . 
     The feature detection unit  742  detects person-related information, which is information to be a feature of a person such as the color of clothes of the person and the belongings of the person, based on image data included by the image information  733 . The feature detection unit  742  may detect information indicating the color of clothes of the person and the belongings of the person by a known technique. For example, in a case where the face authentication apparatus  700  has a function of a posture detection unit or the like (the posture detection unit  243  described in the first example embodiment), the feature detection unit  742  may detect the color of the clothes and the belonging of a person by using the result of detection by the posture detection unit. 
     The magnification instruction unit  743  confirms whether or not the person-related information detected by the feature detection unit  742  is stored as authenticated in the authentication-related information  732 . Then, in a case where the person-related information detected by the feature detection unit  742  is not stored as authenticated in the authentication-related information  732 , the magnification instruction unit  743  instructs the camera  800  to magnify the person having the unstored feature. For example, the magnification instruction unit  743  may instruct to magnify the person and the periphery thereof, or may instruct to magnify the person&#39;s face and the periphery thereof. 
     The face region detection unit  744  detects a face region of a person based on image data included by the image information  733 . As well as the face region detection unit  242 , the face region detection unit  744  can detect a face region by a known technique. 
     As described above, the image information  733  includes image data in which a person or a face is magnified. Therefore, the face region detection unit  744  can detect the face region of the person based on the image data in which the person or the face is magnified. 
     The face authentication unit  745  performs face authentication using the result of detection by the face region detection unit  744 . Then, the face authentication unit  745  associates the face authentication result with person-related information of the authenticated person, and stores as the authentication-related information  732  into the storage unit  730 . 
     Processing in performing the face authentication by the face authentication unit  745  may be the same as that of the face authentication unit  246  described in the first and second example embodiments. Therefore, a description thereof will be omitted. 
     The above is an example of the configuration of the face authentication apparatus  700 . 
     The camera  800  is an imaging device that acquires image data.  FIG.  16    shows an example of a configuration of the camera  800 . Referring to  FIG.  16   , the camera  800  includes, for example, a transmission and reception unit  810 , a zoom setting unit  820 , and an imaging unit  830 . 
     For example, the camera  800  includes an arithmetic logic unit such as a CPU and a storage unit. The camera  800  can realize the above processing units by execution of a program stored in the storage unit by the arithmetic logic unit. 
     The transmission and reception unit  810  transmits and receives data to and from the face authentication apparatus  700 . For example, the transmission and reception  810  transmits image data acquired by the imaging unit  830  to the face authentication apparatus  700 . Moreover, the transmission and reception unit  810  receives a zoom instruction from the face authentication apparatus  700 . 
     The zoom setting unit  820  magnifies a designated person or face based on a zoom instruction received from the face authentication apparatus  700 . The zoom setting unit  820  may perform optical zoom or perform digital zoom based on the zoom instruction. 
     The imaging unit  830  acquires image data. In a case where the zoom setting unit  820  has accepted a zoom instruction, the imaging unit  830  acquires image data in which a person or a face is magnified. The image data acquired by the imaging unit  830  can be associated with time and date when the imaging unit  830  acquires the image data, and transmitted to the face authentication apparatus  700  via the transmission and reception unit  810 . 
     The above is an example of the configuration of the camera  800 . Subsequently, an example of an operation of the face authentication apparatus  700  will be described with reference to  FIG.  17   . 
     Referring to  FIG.  17   , the feature detection unit  742  detects person-related information, which is information to be a feature of a person such as the color of clothes of the person and the belongings of the person, based on image data included by the image information  733  (step S 301 ). 
     The magnification instruction unit  743  confirms whether or not the person-related information detected by the feature detection unit  742  is stored as authenticated in the authentication-related information  732  (step S 302 ). 
     In a case where the person-related information detected by the feature detection unit  742  is not stored as authenticated in the authentication-related information  732  (step S 303 ), the magnification instruction unit  743  instructs the camera  800  to magnify the person having the unstored feature (step S 303 ). For example, the magnification instruction unit  743  may instruct to magnify the person and the periphery thereof, or may instruct to magnify the person&#39;s face and the periphery thereof. 
     The face region detection unit  744  detects a face region of the person based on the image data included by the image information  733  (step S 304 ). Since the magnification instruction unit  743  has instructed to zoom by the process at step S 303 , the face region detection unit  744  can detect the face region of the person based on the image data in which the person or the face is magnified. 
     The face authentication unit  745  performs face authentication using the result of detection by the face region detection unit  744  (step S 305 ). Then, the face authentication unit  745  associates the result of face authentication with the person-related information of the authenticated person, and stores as the authentication-related information  732  into the storage unit  730 . 
     The above is an example of the operation of the face authentication apparatus  700 . 
     Thus, the face authentication apparatus  700  includes the feature detection unit  742 , the magnification instruction unit  743 , and the face region detection unit  744 . With such a configuration, the magnification instruction unit  743  can instruct the camera  800  to magnify a person or a face based on the result of detection by the feature detection unit  742 . As a result, the face region detection unit  744  can perform detection of a face region by using image data in which the person or the face is magnified. Consequently, it becomes possible to perform detection of a face region more accurately. 
     As described above, the face authentication system  600  can include a plurality of cameras  800 . Moreover, the face authentication apparatus  700  can include a function of the face authentication apparatus  200  described in the first example embodiment and the face authentication apparatus  500  described in the second example embodiment. The face authentication system  600  and the face authentication apparatus  700  may have the same modified examples as in the first example embodiment and the second example embodiment. 
     Fourth Example Embodiment 
     Next, a fourth example embodiment of the present invention will be described with reference to  FIGS.  18  and  19   .  FIGS.  18  and  19    show an example of a configuration of a detection apparatus  900   
     The detection apparatus  900  detects a face region of a person based on image data. FIG.  18  shows an example of a hardware configuration of the detection apparatus  900 . Referring to  FIG.  18   , the detection apparatus  900  has, as an example, the following hardware configuration including; 
     a CPU (Central Processing Unit)  901  (arithmetic logic unit), 
     a ROM (Read Only Memory)  902  (storage unit), 
     a RAM (Random Access Memory)  903  (storage unit), 
     programs  904  loaded to the RAM  903 , 
     a storage device  905  for storing the programs  904 , 
     a drive device  906  that reads from and writes into a recording medium  910  outside the information processing apparatus, 
     a communication interface  907  connecting to a communication network  911  outside the information processing apparatus, 
     an input/output interface  908  that inputs and outputs data, and 
     a bus  909  connecting the respective components. 
     Further, the detection apparatus  900  can realize functions as a detection unit  921  and a setting change unit  922  shown in  FIG.  30    by acquisition and execution of the programs  904  by the CPU  901 . The programs  904  are, for example, stored in the storage device  905  or the ROM  902  in advance, and are loaded to the RAM  903  or the like by the CPU  901  as necessary. Moreover, the programs  904  may be supplied to the CPU  901  via the communication network  911 , or may be stored in the recording medium  910  in advance and retrieved and supplied to the CPU  901  by the drive device  906 . 
       FIG.  18    shows an example of the hardware configuration of the detection apparatus  900 . The hardware configuration of the detection apparatus  900  is not limited to the abovementioned case. For example, the detection apparatus  900  may be configured by part of the abovementioned configuration, for example, excluding the drive device  906 . 
     The detection unit  921  performs detection of a face region based on image data acquired by a predetermined imaging device. 
     The setting change unit  922  changes the setting for performing a face region detection process with image data acquired by another imaging device, based on the result of detection by the detection unit  921 . 
     Thus, the detection apparatus  900  includes the detection unit  921  and the setting change unit  922 . With such a configuration, the setting change unit  922  can change the setting for performing a face region detection process with image data acquired by another imaging device, based on the result of detection by the detection unit  921 . As a result, it becomes possible to properly perform parameter adjustment and inhibit failure to detect a face region. 
     The above detection apparatus  900  can be realized by installation of a predetermined program into the detection apparatus  900 . Specifically, a program as another aspect of the present invention is a program for causing the detection apparatus  900  performing detection of a face region based on image data to realize: the detection unit  921  performing detection of a face region based on image data acquired by a predetermined imaging device; and the setting change unit  922  changing the setting for performing a face region detection process with image data acquired by another imaging device, based on the result of detection by the detection unit  921 . 
     Further, a detection method executed by the above detection apparatus  900  is a method including, by the detection apparatus  900  performing detection of a face region based on image data: performing detection of a face region based on image data acquired by a predetermined imaging device; and changing the setting for performing a face region detection process with image data acquired by another imaging device, based on the detection result. 
     A program (a recording medium on which a program is recorded) or a detection method having the above configuration also has the same action and effect as the above detection apparatus  900 , and therefore, can achieve the abovementioned object of the present invention. 
     &lt;Supplementary Notes&gt; 
     The whole or part of the example embodiments disclosed above can be described as the following supplementary notes. Below, the overview of a detection method and others according to the present invention will be described. However, the present invention is not limited to the following configurations. 
     (Supplementary Note 1) 
     A detection method executed by a detection apparatus, the detection method comprising: 
     performing detection of a face region based on image data acquired by a predetermined imaging device; and 
     changing setting for performing a face region detection process with image data acquired by another imaging device, based on a result of the detection. 
     (Supplementary Note 2) 
     The detection method according to Supplementary Note 1, comprising 
     instructing the other imaging device to adjust a parameter used when the other imaging device acquires image data, based on the result of the detection. 
     (Supplementary Note 3) 
     The detection method according to Supplementary Note 1 or 2, comprising 
     adjusting a face detection threshold value used for performing the face region detection process with the image data acquired by the other imaging device, based on the result of the detection. 
     (Supplementary Note 4) 
     The detection method according to any one of Supplementary Notes 1 to 3, comprising 
     in a case where a face region cannot be detected based on the image data acquired by the predetermined imaging device, changing the setting for performing the face region detection process with the image data acquired by the other imaging device. 
     (Supplementary Note 5) 
     The detection method according to any one of Supplementary Notes 1 to 4, comprising 
     in a case where a face region cannot be detected based on the image data acquired by the predetermined imaging device, changing setting for performing the face region detection process with the image data acquired by the predetermined imaging device and performing detection of a face region, and thereafter, changing the setting for performing the face region detection process with the image data acquired by the other imaging device. 
     (Supplementary Note 6) 
     The detection method according to Supplementary Note 5, comprising 
     in a case where a face region cannot be detected based on the image data acquired by the predetermined imaging device, changing setting of a region estimated based on a result of detection of a posture of a person, and also performing detection of a face region on the region estimated based on the result of the detection of the posture of the person. 
     (Supplementary Note 7) 
     The detection method according to any one of Supplementary Notes 1 to 6, comprising 
     in a case where there are a plurality of other imaging devices, estimating an imaging device located ahead in an advancing direction of a person based on a result of detection of a posture of the person, and changing setting for performing the face region detection process with image data acquired by the estimated imaging device. 
     (Supplementary Note 8) 
     The detection method according to any one of Supplementary Notes 1 to 7, comprising 
     detecting a feature of a person, and instructing the imaging device to acquire image data in a state that the person is magnified based on a detected result. 
     (Supplementary Note 9) 
     The detection method according to Supplementary Note 8, comprising 
     in a case where a feature of an undetected person is detected, instructing the imaging device to acquire image data in a state that the person is magnified. 
     (Supplementary Note 10) 
     The detection method according to any one of Supplementary Notes 1 to 9, comprising: 
     performing face authentication based on the result of the detection of the face region; and 
     outputting a result of the face authentication, and information indicating an advancing direction estimated based on a result of detection of a posture of a person identified by the result of the face authentication. 
     (Supplementary Note 11) 
     A detection apparatus comprising: 
     a detection unit configured to perform detection of a face region based on image data acquired by a predetermined imaging device; and 
     a setting change unit configured to change setting for performing a face region detection process with image data acquired by another imaging device, based on a result of the detection by the detection unit. 
     (Supplementary Note 12) 
     The detection apparatus according to Supplementary Note 11, wherein 
     the setting change unit is configured to instruct the other imaging device to adjust a parameter used when the other imaging device acquires image data, based on the result of the detection by the detection unit. 
     (Supplementary Note 13) 
     The detection apparatus according to Supplementary Note 12, wherein 
     the setting change unit is configured to adjust a face detection threshold value used for performing the face region detection process with the image data acquired by the other imaging device, based on the result of the detection by the detection unit. 
     (Supplementary Note 14) 
     The detection apparatus according to any one of Supplementary Notes 11 to 13, wherein 
     the setting change unit is configured to, in a case where the detection unit cannot detect a face region based on the image data acquired by the predetermined imaging device, change the setting for performing the face region detection process with the image data acquired by the other imaging device. 
     (Supplementary Note 15) 
     The detection apparatus according to any one of Supplementary Notes 11 to 14, wherein 
     the setting change unit is configured to, in a case where the detection unit cannot detect a face region based on the image data acquired by the predetermined imaging device, change setting for performing the face region detection process with the image data acquired by the predetermined imaging device and perform detection of a face region, and thereafter, change the setting for performing the face region detection process with the image data acquired by the other imaging device. 
     (Supplementary Note 16) 
     The detection apparatus according to Supplementary Note 15, wherein: 
     the setting change unit is configured to, in a case where the detection unit cannot detect a face region based on the image data acquired by the predetermined imaging device, change setting of a region estimated based on a result of detection of a posture of a person; and 
     the detection unit is configured to perform detection of a face region on the region estimated based on the result of the detection of the posture of the person. 
     (Supplementary Note 17) 
     The detection apparatus according to any one of Supplementary Notes 11 to 16, comprising 
     a move destination estimation unit configured to estimate an imaging device located ahead in an advancing direction of a person based on a result of detection of a posture of the person, 
     wherein the setting change unit is configured to change setting for performing the face region detection process with image data acquired by the imaging device estimated by the move destination estimation unit. 
     (Supplementary Note 18) 
     The detection apparatus according to any one of Supplementary Notes 11 to 17, comprising: 
     a feature detection unit configured to detect a feature of a person; and 
     a magnification instruction unit configured to instruct the imaging device to acquire image data in a state that the person is magnified based on a result detected by the feature detection unit. 
     (Supplementary Note 19) 
     The detection apparatus according to Supplementary Note 18, wherein 
     the magnification instruction unit is configured to, in a case where the detection unit detects a feature of an undetected person, instruct the imaging device to acquire image data in a state that the person is magnified. 
     (Supplementary Note 20) 
     The detection apparatus according to any one of Supplementary Notes 11 to 19, comprising: 
     a face authentication unit configured to perform face authentication based on the result of the detection of the face region; and 
     an output unit configured to output a result of the face authentication by the face authentication unit, and information indicating an advancing direction estimated based on a result of detection of a posture of a person identified by the result of the face authentication by the face authentication unit. 
     (Supplementary Note 21) 
     A non-transitory computer-readable recording medium having a program recorded thereon, the program comprising instructions for causing a detection apparatus to realize: 
     a detection unit configured to perform detection of a face region based on image data acquired by a predetermined imaging device; and 
     a setting change unit configured to change setting for performing a face region detection process with image data acquired by another imaging device, based on a result of the detection by the detection unit. 
     The program described in the example embodiments and supplementary notes is stored in a storage device, or recorded on a computer-readable recording medium. For example, the recording medium is a portable medium such as a flexible disk, an optical disk, a magnetooptical disk, and a semiconductor memory. 
     Although the present invention has been described above with reference to the example embodiments, the present invention is not limited to the example embodiments. The configurations and details of the present invention can be changed in various manners that can be understood by one skilled in the art within the scope of the present invention. 
     DESCRIPTION OF NUMERALS 
     
         
           100  face authentication system 
           200  face authentication apparatus 
           210  screen display unit 
           220  communication IN unit 
           230  storage unit 
           231  information for detection 
           232  trained model 
           233  feature value information 
           234  image information 
           235  posture information 
           236  authentication result information 
           237  program 
           238  information for move destination estimation 
           240  operation processing unit 
           241  image acquisition unit 
           242  face region detection unit 
           243  posture detection unit 
           244  face region estimation unit 
           245  parameter adjustment unit 
           246  face authentication unit 
           247  output unit 
           300  camera 
           310  transmission and reception unit 
           320  setting unit 
           330  imaging unit 
           400  face authentication system 
           500  face authentication apparatus 
           540  operation processing unit 
           545  parameter adjustment unit 
           547  output unit 
           548  move destination estimation unit 
           600  face authentication system 
           700  face authentication apparatus 
           710  screen display unit 
           720  communication IN unit 
           730  storage unit 
           731  information for detection 
           732  authentication-related information 
           733  image information 
           734  program 
           740  operation processing unit 
           741  image acquisition unit 
           742  feature detection unit 
           743  magnification instruction unit 
           744  face region detection unit 
           745  face authentication unit 
           800  camera 
           810  transmission and reception unit 
           820  zoom setting unit 
           830  imaging unit 
           900  detection apparatus 
           901  CPU 
           902  ROM 
           903  RAM 
           904  programs 
           905  storage device 
           906  drive device 
           907  communication interface 
           908  input/output interface 
           909  bus 
           910  recording medium 
           911  communication network 
           921  detection unit 
           922  setting change unit