Patent Publication Number: US-9842269-B2

Title: Video processing apparatus, video processing method, and recording medium

Description:
This application is a continuation application of application Ser. No. 13/917,542, filed on Jun. 13, 2013, which claims the benefit of Japanese Patent Application No. 2012-135834, filed Jun. 15, 2012, which are hereby incorporated by reference herein in their entirety. 
    
    
     BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present invention relates to a video processing apparatus, a video processing method, and a recording medium for detecting a moving object in a video. 
     Description of the Related Art 
     Conventionally, as a method of detecting a moving object in a movie, a method of detecting a moving object based on a difference between a reference image and a current image is known. 
     As a method of detecting an object having a certain feature from a movie, a method of comparing an object in a movie with a predetermined pattern, and detecting an object having a high correlation with the pattern from the movie is known. 
     Japanese Patent Application Laid-Open No. 2011-166243 discloses a monitoring system that detects a moving object from a movie captured by an image capturing apparatus based on a difference between a reference image and a current image, and among a plurality of detected moving bodies, that further detects a moving object satisfying predetermined conditions regarding a size, a moving speed, or the like. 
     Japanese Patent Application Laid-Open No. 2009-211311 discloses an image processing apparatus that performs detection using a plurality of local feature amounts extracted from a collation pattern upon detection of a human body from an image by collating the collation pattern with a whole image. 
     According to the conventional method in which only a method of detecting a moving object (referred to as moving object detection, hereinafter) is used, a moving object that is not an actual target of detection may be detected. 
     According to the conventional method in which only a method of detecting an object having a high correlation with the predetermined pattern (referred to as object detection, hereinafter) is used, a moving object cannot be detected. 
     In order to solve these problems, moving object detection and object detection are preferably used together, but the following problem arises to realize such a method. 
     That is, when a moving object having a certain shape exists in a movie, a region in which the moving object is detected by the moving object detection and a region in which the moving object is detected by the object detection do not necessarily match with each other. Therefore, a certain moving object cannot be accurately detected by collating the result of the moving object detection and the result of the object detection. 
     For example, in the moving object detection, only a moving part of a certain moving object in a movie may be detected. 
     SUMMARY OF THE INVENTION 
     A video processing apparatus of the present invention is configured as follows. 
     That is, a video processing apparatus includes: a first detection unit configured to detect a moving object from a movie; a second detection unit configured to detect an object having a predetermined shape from the movie; an extraction unit configured to extract a partial region of a region in which the second detection unit has detected the object having the predetermined shape in the movie; and a discrimination unit configured to discriminate whether the object detected by the second detection unit is a certain object depending on a ratio of a size of an overlapping region to a size of an extracted region extracted by the extraction unit, the overlapping region being a region where a region in which the first detection unit has detected the moving object in the movie and the extracted region overlap with each other. 
     Further features of the present invention will become apparent from the following description of exemplary embodiments (with reference to the attached drawings). 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a diagram illustrating a configuration of a video processing apparatus; 
         FIGS. 2A, 2B and 2C  are diagrams illustrating a configuration of a control unit  103  according to a first embodiment; 
         FIG. 3  is a process flow chart of the video processing apparatus according to the first embodiment; 
         FIG. 4  is a process flow chart of a determination process according to the first embodiment; 
         FIG. 5  is a view for illustrating an example of the determination process; 
         FIG. 6  is a process flow chart of a discrimination process according to the first embodiment; 
         FIG. 7  is a view for illustrating a moving object region, an object region and an extracted region; and 
         FIG. 8  is a view for illustrating an overlapping region. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     Hereinafter, the present invention will be described in detail based on preferred embodiments with reference to the accompanying drawings. Note that the configurations shown in the following embodiments are merely examples, and the present invention is not limited to the illustrated configurations. 
     First Embodiment 
     A configuration of a video processing apparatus  100  according to this embodiment will be described with reference to  FIG. 1 . An acquisition unit  101  acquires a video from a camera, server, an external memory, or the like. 
     A storage unit  102  stores the movie acquired by the acquisition unit  101 . When a control unit  103  to be described below incorporates a processor such as a Central Processing Unit (CPU), the storage unit  102  stores a program to be executed by the processor. In addition, the storage unit  102  is used to store parameters temporarily that are used upon execution of the program by the processor executes when the control unit  103  incorporates the processor. The storage unit  102  may be configured with a Random Access Memory (RAM), Read Only Memory (ROM), or the like, for example. In addition, an external storage device or a removable medium may be used as the storage unit  102 . The storage unit  102  may be configured by a plurality of hardware units. For example, the storage unit  102  may be configured by a temporary storage unit used to store temporary data, an auxiliary storage unit configured to store the program, etc., and the like. 
     The control unit  103  detects a moving object from a movie acquired by the acquisition unit  101  (first detection). The control unit  103  detects an object that matches with a predetermined pattern from the video acquired by the acquisition unit  101  (second detection). The control unit  103  also identifies a predetermined moving object from the video acquired by the acquisition unit  101  using the moving object detection result and the object detection result. Then, the control unit  103  determines whether the identified moving object has passed over a detection line that is set on the video. The control unit  103  also controls operations of the components of the video processing apparatus  100  according to this embodiment. 
     An output unit  105  outputs a result of determination by the control unit to an external device. A bus  104  connects the above-described components. 
     Next, a functional block diagram of the control unit  103  is illustrated in  FIG. 2A . When the control unit  103  incorporates a processor, functions respectively illustrated in blocks of  FIG. 2A  are implemented by the processor executing the program stored in the storage unit  102 . Alternatively, a part of or the whole of the functions respectively illustrated in blocks of  FIG. 2A  may be implemented by individual hardware units. 
     An acquisition control unit  201  controls the acquisition unit  101  to acquire a video from the outside and controls the storage unit  102  to store the video. 
     A first detection unit  202  detects a region of a moving object (moving object region) from the video (movie) acquired by the acquisition unit  101 . As a method of detecting a moving object in a movie, a background subtraction method can be used, for example, but a method of detecting a moving object is not limited thereto. The detection by the first detection unit  202  can be any detection capable of identifying a position and a size of a moving object in a movie. As a size of a moving object, a height and a width of a circumscribing rectangle of the moving object may be identified. A region of a moving object (moving object region) may be defined as a circumscribed rectangular region of the moving object detected by the first detection unit  202 , for example. 
     A determination unit  203  determines a detection region, in which a process of detecting a predetermined object is performed, on a movie screen image (on a movie) according to the detection result by the first detection unit  202 . A functional block diagram of the determination unit  203  is illustrated in  FIG. 2B . An identification unit  211  sets a region of the each moving object detected by the first detection unit  202  (circumscribing rectangle). A region setting unit  212  enlarges the region set by the identification unit  211  based on a predetermined set value to create an enlarged region. An overlap judgement unit  213  judges whether a plurality of enlarged regions overlaps with each other. When a plurality of enlarged regions overlaps with each other, a composition unit  214  sets a new enlarged region that covers the enlarged regions (a rectangle covering the plurality of enlarged regions, for example). The detail of a process of determining a detection region performed by the determination unit  203  will be described below with reference to  FIGS. 4 and 5 . 
     A second detection unit  204  performs a detection process for detecting a predetermined object in the detection region determined by the determination unit  203 . Note that the predetermined object is an object having a certain feature amount in a part or the whole of an object. For example, when a human body is detected, the detection can be performed by judging whether an object has a circular feature corresponding to a head of a human body, and has a feature of a shape corresponding to shoulders of a human body. The object detection process may be performed using a pattern matching process, for example. However, the detection process performed by the second detection unit  204  is not limited to the pattern matching process, and can be can be any detection capable of identifying a position and a size of an object that has a predetermined shape. As a size of an object, a height and a width of a circumscribing rectangle of the detected object may be identified. An object that is detected by the detection process may be a human body, a face, a car, an animal, or the like, for example. 
     An extraction unit  205  extracts an extracted region from a region of an object detected by the second detection unit  204  in the movie. The region of the object detected by the second detection unit  204  (object region) may be a circumscribed rectangular region of the object detected by the second detection unit  204 , for example. 
     The extracted region used herein is a partial region of the object region in which the second detection unit  204  detects the predetermined object, and is a region used for a discrimination process by a discrimination unit  206  to be described below. 
     For example, the extracted region may be a region covering a predetermined ratio of the object region. Alternatively, the extracted region may be a rectangular region that is at a predetermined position in the object region and that has a predetermined height. For example, the extracted region may be defined to be a rectangular region that is an upper region of the object region detected by the second detection unit  204  and that has a half height of the object region. That is, when the second detection unit  204  detects a human body, a region representing an upper body of a human body may be the extracted region. 
     Alternatively, the extracted region may be a part of the detected object that is a part having a predetermined shape (local feature amount) or a circumscribed rectangular region of the part. For example, when the second detection unit  204  detects a human body, a region representing any of a human body part such as a region of a head, a face, face organs, a shoulder, an arm, a chest, and a leg may be defined as an extracted region. 
     When the second detection unit  204  detects a face, a region representing an eye, a nose, an ear, or the like may be defined as an extracted region. When the second detection unit  204  detects a car, a region representing a license plate, a headlight, a side mirror, or the like may be defined as an extracted region. When the second detection unit  204  detects an animal, a region representing a face, a body, a tail, or the like of an animal may be defined as an extracted region. 
     The discrimination unit  206  discriminates whether the detection result of the second detection unit  204  is a correct detection or an erroneous detection.  FIG. 2C  illustrates a functional block diagram of the discrimination unit  206 . A size discrimination unit  221  judges whether a size of a certain object detected by the second detection unit  204  is within a size range defined by an object size range value set by a setting unit  208  to be described below. An overlap discrimination unit  222  discriminates whether a ratio of an overlapping region to an extracted region is within a range defined by an overlapping region range value, the extracted region being extracted by the extraction unit  205 , and the overlapping region being a region where a region of a moving object detected by the first detection unit  202  and the extracted region overlap with each other. A region of a moving object (moving object region) is a circumscribed rectangular region of a moving object detected by the first detection unit  202 , for example. The overlapping region range value is a value set by the setting unit  208  to be described below. The detail of the discrimination process performed by the discrimination unit  206  will be described below with reference to  FIG. 6 . 
     Regarding a detected object that has been discriminated as a correctly detected object by the discrimination unit  206 , a tracking unit  207  associates the detected object in a first frame image included in a movie with the detected object in a second frame image included in the movie. The tracking unit  207  appends an identical track ID (identifier) to an image of the detected object in the first frame image, and an image of the detected object in the second frame image. In addition, the tracking unit  207  appends a new unique track ID to an object newly detected by the second detection unit  204 . 
     The setting unit  208  sets a region to be extracted by the above-described extraction unit  205  in an object region. For example, a rectangular region that is an upper region of the circumscribed rectangular region of the object region detected by the second detection unit  204  and that has a half height of the circumscribed rectangular region may be set as an extracted region. Alternatively, a region having a certain feature amount in the object region may be set as an extracted region. The way of setting is not limited thereto. 
     The setting unit  208  sets the object size range value used by the discrimination unit  206  to discriminate whether a size of an object detected by the second detection unit  204  is within a predetermined size range. For example, the setting unit  208  sets maximum values and minimum values of a width and a height of a circumscribing rectangle of a detected object as object size range values. 
     The setting unit  208  sets an overlapping region range value used by the discrimination unit  206  to perform the above-described discrimination process. The overlapping region range value used herein is a value that defines a range of a ratio of an overlapping region to an extracted region, the extracted region being extracted by the extraction unit  205 , and the overlapping region being a region where the extracted region and a region detected by the second detection unit  204  overlap with each other. For example, the overlapping region range value may define a range of a ratio of the overlapping region to the extracted region extracted by the extraction unit  205 . For example, the overlapping region range value may be set to be 60% or more and 100% or less of an area of the extracted region. The overlapping region range value may be used to set either one of the maximum value and the minimum value of the ratio of an overlapping region. 
     In addition, the setting unit  208  sets a detection line used by a pass discrimination unit  209  to be described below to perform pass discrimination. 
     Each of the set values to be set by the setting unit  208  can be set by an operator who operates the video processing apparatus  100 . Alternatively, the setting unit  208  may previously retain the set values. 
     The pass discrimination unit  209  discriminates whether an object being tracked by the tracking unit  207  has passed over the detection line set by the setting unit  208 . The pass discrimination is performed by discriminating whether a trail of the object from a first frame image to a second frame image that is captured later than the first frame image intersects with the detection line where the frame images are included in a movie. The pass discrimination unit  209  may count the number of passes of the object being tracked over the detection line. 
     An output control unit  210  causes the output unit  105  to output the pass discrimination result by the pass discrimination unit  209 . 
     Next, an operation of the video processing apparatus  100  according to this embodiment will be described with reference to  FIG. 3 . In a case where the control unit  103  incorporates a processor, the process flow of  FIG. 3  represents a program that causes the processor to execute procedures illustrated in  FIG. 3 . The processor incorporated in the control unit  103  may be a computer, and the computer executes a program read out from a memory incorporated in the video processing apparatus  100 . 
     First, the acquisition control unit  201  of the control unit  103  causes the acquisition unit  101  to acquire a movie (S 301 ) (acquisition procedure). 
     Next, the first detection unit  202  performs a moving object detection process for detecting a moving object in the acquired movie (S 302 ) (first detection procedure). For the moving object detection process, a background subtraction method may be used, for example. 
     The control unit  103  discriminates whether the first detection unit  202  detects a moving object in the movie (S 303 ). If the first detection unit  202  has not detected any moving object in the movie (No in S 303 ), the control unit  103  ends the process. On the other hand, if the first detection unit  202  has detected a moving object in the movie (Yes in S 303 ), the determination unit  203  determines a detection region in which the second detection unit  204  performs detection out of the region in the movie (S 304 ) (determine procedure). 
     The detection region is determined based on the result of the moving object detection performed by the first detection unit  202  in step S 302 . Since the second detection unit  204  limits a region in which detection is performed, a load of the detection process can be reduced. In addition, since the detection region is determined based on the result of the moving object detection, a region in which a subject to be detected likely exists can be determined as the detection region. The detail of the process of determining the detection region will be described below with reference to  FIG. 4 . 
     After the determination unit  203  determines the detection region, the second detection unit  204  performs a detection process of detecting a predetermined object in the detection region determined by the determination unit  203  (S 305 ) (second detection procedure). For this detection process, a pattern matching process can be used, for example. 
     The control unit  103  discriminates whether the second detection unit  204  has detected a predetermined object in the detection region (S 306 ). If the second detection unit  204  has not detected the predetermined object (No in S 306 ), the control unit  103  ends the process. On the other hand, if the second detection unit  204  has detected the predetermined object (Yes in S 306 ), the extraction unit  205  extracts the above-described extracted region from a region of the detected predetermined object (S 307 ) (extraction procedure). For example, when the second detection unit  204  detects a human body, a region representing an upper body of a human body may be the extracted region. 
     Next, the discrimination unit  206  discriminates whether the detection result of the second detection unit  204  is correct based on the position and the size of the extracted region extracted in step S 307 , and the position and the size of the moving object detected by the first detection unit  202  (S 308 ) (discrimination procedure). The detail of the discrimination process in step S 308  will be described below with reference to  FIG. 6 . 
     Next, the tracking unit  207  performs a tracking process of tracking the object that has been detected by the second detection unit  204  in step S 308  and that is a detected object that has been discriminated as a correctly detected object by the discrimination unit  206  (S 309 ). That is, the tracking unit  207  performs a process of associating the detected object in the first frame image with the detected object in the second frame image regarding the detected object that has been discriminated as a correctly detected object by the discrimination unit  206 , the frame images being included in the movie. 
     The pass discrimination unit  209  discriminates whether the object being tracked by the tracking unit  207  has passed over the predetermined detection line (S 310 ) (pass discrimination procedure). The output control unit  210  performs a control of outputting the result of determination of the pass discrimination unit  209  from the output unit  105  (S 311 ) (output control procedure). Then, the control unit  103  ends the process. 
     Next, a determination process of determining the detection region performed by the determination unit  203  in step S 304  will be described with reference to a flow chart of  FIG. 4 . In a case where the control unit  103  incorporates a processor, the process flow of  FIG. 4  represents a program that causes the processor to execute procedures illustrated in  FIG. 4 . The processor incorporated in the control unit  103  may be a computer, and the computer executes a program read out from a memory incorporated in the video processing apparatus  100 . 
     In this embodiment, first, the identification unit  211  of the determination unit  203  sets circumscribing rectangles of the respective moving bodies detected by the first detection unit  202  (S 401 ).  FIG. 5  illustrates an example of detection result of the moving bodies. In the example of  FIG. 5 , a moving object is illustrated as a grouped region of some of sectioned regions that are obtained by sectioning the screen image of the acquired movie into a plurality of regions. Each of the sectioned regions is a minimum unit to detect presence/absence of movement in the movie. Each of the sectioned regions may be one pixel, and may be a region including a plurality of pixels. Colored regions  506 ,  507  illustrated in  FIG. 5  represent moving object regions. Rectangles  501 ,  502  that circumscribe the regions  506 ,  507  representing moving bodies are the circumscribing rectangles of the moving bodies. 
     After the first detection unit  202  sets a circumscribing rectangle of the each detected moving object, the region setting unit  212  of the determination unit  203  subsequently enlarges the set circumscribing rectangles  501 ,  502 , and sets enlarged regions  503 ,  504  (S 402 ). The region setting unit  212  enlarges the circumscribing rectangles  501 ,  502  based on an enlarging set value set by the setting unit  208 . For example, the enlarging set value may be an enlargement factor used for enlarging a circumscribing rectangle in four vertex directions. The enlarging set value may be a width value by which a circumscribing rectangle is enlarged in four border directions. 
     Next, the determination unit  203  judges whether the first detection unit  202  has already enlarged circumscribing rectangles for all of the detected moving bodies (S 403 ). If there is a moving object for which a circumscribing rectangle has not yet been enlarged (No in S 403 ), the determination unit  203  repeats the process of steps S 401  and S 402 . 
     On the other hand, if the determination unit  203  judges that the first detection unit  202  has already enlarged circumscribing rectangles for all of the detected moving bodies (Yes in S 403 ), the determination unit  203  discriminates whether the plurality of enlarged regions overlaps with each other (S 404 ). 
     If a plurality of enlarged regions overlaps with each other, the composition unit  214  of the determination unit  203  sets a new enlarged region covering their enlarged regions (a rectangle covering the plurality of enlarged regions, for example) (S 405 ). In the example of  FIG. 5 , the enlarged region  503  and the enlarged region  504  overlap with each other. Therefore, a new enlarged region  505  covering the enlarged regions  503 ,  504  is formed. 
     The process of steps S 404  and S 405  is repeated, and when no enlarged regions overlap with each other, the determination unit  203  ends the process. The determination unit  203  determines thus formed enlarged regions as detection regions in which a human body detection process is performed. 
     As described above, when a first enlarged region and a second enlarged region overlap with each other, the determination unit  203  determines a region covering the first enlarged region and the second enlarged region as detection regions in which the second detection unit  204  performs detection. 
     The first enlarged region is a region obtained by enlarging a first region in which the first detection unit  202  detects a first moving object in the movie. The second enlarged region is a region obtained by enlarging a second region in which the first detection unit  202  detects a second moving object in the movie. 
     Since a region in which the second detection unit  204  performs detection is limited as described above, a load of the detection process can be reduced. In addition, since the detection region is determined based on the result of the moving object detection, a region in which a subject to be detected likely exists can be determined as the detection region. 
     Next, the discrimination process performed by the discrimination unit  206  in the process of step S 308  in  FIG. 3  will be described with reference to the flow chart of FIG.  6 . In a case where the control unit  103  incorporates a processor, the process flow of  FIG. 6  represents a program that causes the processor to execute procedures illustrated in  FIG. 6 . The processor incorporated in the control unit  103  may be a computer, and the computer executes a program read out from a memory incorporated in the video processing apparatus  100 . 
     First, the size discrimination unit  221  of the discrimination unit  206  judges whether a size of a certain object detected by the second detection unit  204  is within a size range defined by the object size range value set by the setting unit  208  (S 601 ). For example, the size discrimination unit  221  judges whether the width and the height of a circumscribing rectangle of an object detected by the second detection unit  204  is in width and height ranges defined by range values set by the setting unit  208 . As described above, only an object having a predetermined size can be detected out of detected objects that have been detected by the second detection unit  204 . 
     If the size of an object detected by the second detection unit  204  is out of the size range defined by the range value (No in S 601 ), the discrimination unit  206  discriminates that the detection is an erroneous detection. On the other hand, if the size of an object detected by the second detection unit  204  is within the size range defined by the range value (Yes in S 601 ), a process of step S 602  is performed. 
     In step S 602 , the overlap discrimination unit  222  of the discrimination unit  206  discriminates whether a ratio of an overlapping region to an extracted region is within a range defined by the overlapping region range value, the extracted region being extracted by the extraction unit  205 , and the overlapping region being a region where the extracted region and a region of a moving object detected by the first detection unit  202  overlap with each other. The way of defining an overlapping region range is not limited to a case where a maximum and a minimum are defined, but overlapping region range value may be defined as a predetermined ratio or more. 
     The overlapping region will be described next with reference to  FIGS. 7 and 8 . A moving object region  701  of  FIG. 7  represents a region in which the first detection unit  202  has detected a moving object. The moving object region  701  illustrated in  FIG. 7  is an example of a detection result when a movement is detected only in an upper body of a human body. For example, in a moving object detection method such as a background subtraction method, whether a moving object is a certain object such as a human body is not considered, only a part of a certain object may be detected as a moving object as the moving object region  701  illustrated in  FIG. 7 . 
     An object region  702  represents a region in which the second detection unit  204  has detected a certain object (human body in the example of  FIG. 7 ). An extracted region  703  represents a region that is a part region of the object region  702 , and that is extracted by the extraction unit  205 . In the example of  FIG. 7 , the object region  702  is a region illustrated by a circumscribing rectangle of an object detected by the second detection unit  204 . The extracted region  703  is a region that is represented by a rectangle having a height of a predetermined ratio of the height of the object region  702  and that is positioned on the upper part of the object region  702 . The extracted region  703  in  FIG. 7  represents an example where an upper body region of the detected human body is extracted. 
     A screen image  801  in  FIG. 8  illustrates one screen image included in the movie acquired by the acquisition unit  101 . A detection region  802  and a detection region  803  represent regions in the screen image  801  determined as described above by the determination unit  203  as regions in which the object detection is to be performed. The detection region  802  is a rectangle covering enlarged regions  505  and  804  that overlap with each other. The enlarged region  505  is a rectangle covering the enlarged regions  503  and  504  that overlap with each other as described with reference to  FIG. 5 . The detection region  803  is a rectangle covering enlarged regions  805  and  806  that overlap with each other. 
       FIG. 8  illustrates an example where the moving object region  701  is detected in the detection region  802 , and at an identical position, the object region  702  is detected. In this case, a region where the moving object region  701  and the extracted region  703  overlap with each other is an overlapping region. Based on a ratio of the size of this overlapping region to the size of the extracted region  703 , it is discriminated whether the detection of the object region  702  is correct detection. For other moving object regions illustrated in  FIG. 8 , collation with the detected object region is similarly performed. The size of an overlapping region may be defined as an area of the overlapping region, for example. The size of an extracted region may be defined as an area of the extracted region, for example. 
     With reference to  FIG. 8 , an example where the moving object region  701  is included in the object region  703  is described. However, their relation is not limited thereto and the moving object region  701  may be beyond the object region  703 . For example, when a human body and its shadow are detected as a moving object of one cluster, the moving object region  701  may be beyond the object region  703 . 
     When a ratio of the overlapping region to the extracted region  703  is within a range defined by the overlapping region range values, the detection is judged to be correct detection (S 603 ), and the process is ended. On the other hand, when the ratio of the overlapping region is out of a range defined by the overlapping region range values, the detection is discriminated as erroneous detection (S 604 ), and the process is ended. 
     Thus, for example, when the ratio of the overlapping region to the extracted region  703  is large, it can be discriminated that the moving object detected by the first detection unit  202  is likely to be a target subject to be detected. On the other hand, when the ratio of the overlapping region to the extracted region is small, it can be discriminated that the moving object detected by the first detection unit  202  is likely not to be a target subject to be detected. 
     When object detection is performed by either the moving object detection process or the object detection process, a subject to be detected that is not a target may be detected. However, by a method according to this embodiment, a subject to be detected is determined based on the result of comparing the result of the moving object detection process and the result of the object detection process. Therefore, a target object can be detected more accurately. 
     In addition, in this embodiment, the extracted region  703  that is a part of region extracted from the object region  702  detected by the object detection process is compared with the moving object region  701 . Thus, a target object can be detected more accurately. 
     By the moving object detection, whole of an object of shooting is not necessarily detected depending on a state where the object of shooting is shot. For example, when a human body is detected, there may be cases such as where an upper body part is detected by the first detection unit  202  because of its movement, while a lower body part is not detected by the first detection unit  202  because of its quiescent. 
     In such a case, the ratio of the overlapping region to the object region  702  (whole human body) is relatively small. Note that the overlapping region is a region where the object region  702  (whole human body) detected by the second detection unit  204  and the moving object region  701  (in a case where only an upper body part is detected) detected by the first detection unit  202  overlap with each other. Thus, the detection may be discriminated as erroneous detection by a method of discriminating detection as correct detection when a ratio of the overlapping region to whole of the object region  702  rather than to the extracted region  703  is a predetermined ratio or more, for example. 
     On the other hand, according to this embodiment, the extracted region  703  that is an extracted part of the object region  702  detected by the second detection unit  204  and the detected moving object region  701  are compared. Thus, the ratio of the overlapping region to the extracted region  703  (upper body part) that has been extracted by the extraction unit  205  is relatively large. Note that the overlapping region is a region where the extracted region  703  and the moving object region  701  (in a case where only an upper body part is detected) detected by the first detection unit  202  overlap with each other. Therefore, according to this embodiment, even if only a part of an actual object is detected as the moving object region  701 , the detection can be discriminated as correct detection. 
     A region extracted by the extraction unit  205  may be defined to be a region having a shape of a part that is particularly notable among parts of an object as a subject to be detected. For example, a head part may be extracted from whole of a human body. Thus, even when an area of an overlapping region of the moving object region  701  and the extracted region  703  is small, a region of the part of the object as a subject to be detected may be detected as correct detection if a ratio of a moving region in a head is large. 
     Thus, according to the first embodiment of the present invention, a target moving object can be accurately detected. Therefore, object tracking, pass detection, pass count, and the like can be more accurately performed when the detection result is used for a tracking process, and a pass detection process. 
     According to the present invention configured as described above, a certain object of shooting can be accurately detected from a movie. 
     Second Embodiment 
     In this embodiment, a configuration in which enlarged regions overlapping with each other are respectively determined as detection regions in a process of determining detection regions. A configuration for preventing repeated detection of an identical object of shooting in such a case will be described. 
     As described in the first embodiment, the second detection unit  204  detects a certain object in a detection region that has been determined by the determination unit  203 . When the determination unit  203  sets a first detection region and a second detection region on a movie, a certain object is detected in each of the regions. 
     Therefore, when the first detection region and the second detection region overlap with each other, if a certain object exists in the overlapping region, the identical object of shooting is repeatedly detected. 
     For example, when a certain object A exists in the overlapping region, the second detection unit  204  detects the certain object A in the first detection region. In addition, the second detection unit  204  detects the certain object A also in the second detection region. 
     When each enlarged region is determined as a detection region as described above, an identical object may be repeatedly detected. Therefore, in this embodiment, there is provided a unit configured to judge the repeatedly detected objects as an identical object, whereby an identical object is not repeatedly detected. 
     A configuration of this embodiment will be described. When enlarged regions overlap with each other, the determination unit  203  in this embodiment does not compose the enlarged regions. When the second detection unit  204  of the video processing apparatus  100  according to this embodiment detects a first object and a second object that are identical object of shooting, a judgement unit included in the second detection unit  204  judges the objects as an identical object. Other than this point, the configuration is identical to that described in the first embodiment, and thus the redundant description thereof will be avoided. 
     Next, an operation of the video processing apparatus  100  according to this embodiment will be described. 
     The determination unit  203  of this embodiment does not perform the process of step S 404  and the process of step S 405  of  FIG. 4  in the detection region determination process (S 304 ). 
     When an identical object of shooting is repeatedly detected in the process of step S 305  of  FIG. 3 , the video processing apparatus  100  according to this embodiment judges them as an identical object. Then, the video processing apparatus  100  detects the object of shooting detected in a first detection region and the object of shooting detected in a second detection region are detected as one object of shooting. 
     The second detection unit  204  discriminates whether a plurality of determination regions determined by the determination unit  203  overlaps with each other. If it is discriminated that the plurality of determination regions overlaps with each other, the second detection unit  204  discriminates whether an identical object of shooting is detected. 
     The second detection unit  204  judges a plurality of detection results as an identical object detection if a ratio of an overlapping region of circumscribing rectangles of object regions of the detected plurality of objects is a predetermined ratio or more. That is, the second detection unit  204  judges a ratio of an overlapping region of a circumscribed rectangular region of a certain object that has been detected in the first detection region and a circumscribed rectangular region of a certain object that has been detected in the second detection region. Then, if the ratio of the overlapping region is the predetermined ratio or more, the second detection unit  204  judges that the object detected in the first detection region and the object detected in the second detection region are an identical object. 
     The judgement whether a plurality of detected objects is an identical object can be made by forming circumscribing rectangles based on positions, widths, and heights thereof on a screen image obtained from the second detection unit  204 , and judging whether an overlap rate of the circumscribing rectangles is within a predetermined range. The overlap rate used herein is a ratio of an overlapping region to the circumscribed rectangular region of one of the object regions. 
     According to this embodiment, it is possible to prevent repeated detection of an identical object of shooting. Therefore, a target object of shooting can be detected more accurately. 
     Other Embodiments 
     Embodiments of the present invention can also be realized by a computer of a system or apparatus that reads out and executes computer executable instructions recorded on a storage medium (e.g., non-transitory computer-readable storage medium) to perform the functions of one or more of the above-described embodiment(s) of the present invention, and by a method performed by the computer of the system or apparatus by, for example, reading out and executing the computer executable instructions from the storage medium to perform the functions of one or more of the above-described embodiment(s). The computer may comprise one or more of a central processing unit (CPU), micro processing unit (MPU), or other circuitry, and may include a network of separate computers or separate computer processors. The computer executable instructions may be provided to the computer, for example, from a network or the storage medium. The storage medium may include, for example, one or more of a hard disk, a random-access memory (RAM), a read only memory (ROM), a storage of distributed computing systems, an optical disk (such as a compact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memory card, and the like. 
     While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.