Patent Publication Number: US-8531547-B2

Title: Image processing apparatus and image processing method

Description:
This is a continuation of Ser. No. 12/396,128 filed 2 Mar. 2009, the entire contents of which are herein incorporated by reference. 
    
    
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to an image processing apparatus such as a video camera and an image processing method, and more particularly, to an image processing apparatus and an image processing method which recognize an object and control image processing. 
     2. Description of the Related Art 
     There have recently appeared a still camera, a monitoring camera, and the like, which recognize a portion to be regarded such as a face of an object from an image being captured, and perform camera control such as focus and exposure in accordance with the portion. 
     For example, a still camera as follows is known. The camera detects a plurality of faces from a captured image, and in the case of finding a face corresponding to that of a person registered in its main body, the camera controls focus and exposure in accordance with the face portion prioritizing the face, and displays a frame with respect to the face portion (e.g. Japanese Laid-Open Patent Publication (Kokai) No. 2004-320287). 
     Further known is a still camera that controls focus prioritizing a central portion from among a plurality of ranging portions to capture an image (e.g. Japanese Laid-Open Patent Publication (Kokai) No. 07-140374). 
     Moreover known is an auto-tracking camera that determines a motion vector, which was detected in the largest number among a plurality of motion vector detection frames, as a vector of a principal object (e.g. Japanese Laid-Open Patent Publication (Kokai) No. 05-030407). 
     However, as to the conventional camera, when another person gets into an image capturing range while the user is capturing an image of a intended person&#39;s face, focus and exposure might be controlled in accordance with another person&#39;s face against the user&#39;s expectation. Further, a frame might be displayed on another person&#39;s face against the user&#39;s expectation. 
     In the case of a still camera, the user can operate the camera so as to prioritize a intended object before a shutter release. But in the case of a video camera, since consecutive image capturing is performed, when focus and exposure with respect to a intended person get off the control, a large problem may occur, such as a problem of desired image quality becoming unobtainable. 
     In the case of the still camera disclosed in Japanese Laid-Open Patent Publication (Kokai) No. 2004-320287, processing for determining consistency with an already registered person&#39;s face is necessary to discriminate an intended object. This causes problems of complex hardware and longer software processing time. 
     The still camera disclosed in Japanese Laid-Open Patent Publication (Kokai) No. 07-140374 has a problem of prioritizing a person in contradiction to the user&#39;s expectation in such a case where a passerby or the like passes behind a person as an object to be captured in the center of the image capturing range. 
     The auto-tracking camera disclosed in Japanese Laid-Open Patent Publication (Kokai) No. 05-030407 might prioritize and capture a person in contradiction to the user&#39;s expectation in such a case where a passerby or the like passes near side of a person as an object to be captured in the image capturing range. 
     SUMMARY OF THE INVENTION 
     The present invention provides an image processing apparatus and an image processing method which are capable of more appropriately auto-selecting an object to be prioritized from among a plurality of detected objects. 
     Accordingly, in a first aspect of the present invention, there is provided an image processing apparatus comprising a characteristic detecting unit that detects a previously set characteristic portion of an object from an image signal constituting a moving image, and a control unit that sets a priority to each characteristic portion when a plurality of the characteristic portions are detected by the characteristic detecting unit and sets a high priority to a characteristic portion being detected for a long period of time. 
     Moreover, in a second aspect of the present invention, there is provided an image processing method comprising the steps of detecting a previously set characteristic portion of an object from an image signal constituting a moving image, and setting a priority to each characteristic portion when a plurality of the characteristic portions are detected, the step of setting a priority includes setting a high priority to a characteristic portion being detected for a long period of time. 
     According to the present invention, it is possible to appropriately control image processing on an object more appropriately auto-selected from among a plurality of detected objects. 
     The features and advantages of the invention will become more apparent from the following detailed description taken in conjunction with the accompanying drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of a digital video camera as an image processing apparatus according to an embodiment of the present invention. 
         FIG. 2  is a view showing an example of an output image of the digital video camera, outputted to an LCD or an external output device shown in  FIG. 1 . 
         FIG. 3  is a view showing an example of an output image after the lapse of a predetermined period of time from the time when the output image of  FIG. 2  was obtained. 
         FIG. 4  is a view showing an example of an output image after the lapse of a predetermined period of time from the time when the output image of  FIG. 3  was obtained. 
         FIG. 5  is a flowchart showing a procedure of object list updating processing that is implemented by the digital video camera shown in  FIG. 1 . 
         FIG. 6  is a view showing an example of an object list stored in a RAM shown in  FIG. 1 . 
         FIG. 7  is a view showing another example of the output image of the digital video camera, outputted to the LCD or the external output device shown in  FIG. 1 . 
         FIG. 8  is a view showing an example of an output image after the lapse of a predetermined period of time from the time when the output image of  FIG. 7  was obtained. 
         FIG. 9  is a view showing an example of an output image after the lapse of a predetermined period of time from the time when the output image of  FIG. 8  was obtained. 
         FIG. 10  is a graph showing scores with respect to distances of an object in the digital video camera shown in  FIG. 1 . 
         FIG. 11  is a graph showing scores with respect to widths of the object in the digital video camera shown in  FIG. 1 . 
         FIG. 12  is a graph showing scores with respect to detection time of the object in the digital video camera shown in  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     The present invention will now be described in detail below with reference to the accompanying drawings showing preferred embodiments thereof. 
       FIG. 1  is a block diagram of an image processing apparatus according to the embodiment of the present invention. Here, as the image processing apparatus, a digital video camera (image pickup apparatus) that records a moving image in a disk-shaped storage medium is taken as an example. 
     As shown in  FIG. 1 , a digital video camera  100  is provided with a CPU  101 , a RAM  102 , a ROM  103 , an operating section  104 , and an internal bus  105  as a control system block. 
     The CPU  101  is connected to the RAM  102 , the ROM  103  and each of other blocks through the internal bus  105 , and controls each block by a control program stored in the ROM  103 . 
     The CPU  101  uses the RAM  102  as a storage device for temporary data at the time of operation. The operating section  104  connected to the CPU  101  has a variety of operational levers and buttons which are operated by the user, and information inputted by these operations is transmitted to the CPU  101 . The CPU  101  can perform a variety of processing in accordance with a direction of the user (namely, the input information). 
     Further, as shown in  FIG. 1 , the digital video camera  100  is provided with a focus lens  110 , an aperture  111 , a lens driver  112 , a CCD image sensor (CCD)  113 , and an AFE  114  as a camera system block. 
     Light having passed through the focus lens  110  forms an image on an image pickup surface of the CCD image sensor  113 , and the optical image on the image pickup surface is converted into an electrical signal. 
     The lens driver  112  drives the focus lens  110  and the aperture  111  by control of the CPU  101  to adjust focus and an aperture amount. Based on a shutter speed directed by the CPU  101 , the AFE  114  drives the CCD image sensor  113  to read an image signal so as to perform sample and hold the image signal, amplify the signal and convert the signal into a digital signal. 
     As shown in  FIG. 1 , the digital video camera  100  is provided with an image inputting section  120 , an image processing section  121 , a buffer memory  122 , a focus evaluating section  123 , an exposure evaluating section  124 , and a characteristic detecting section  125  as an image processing system block. 
     By control of the CPU  101 , an image signal is inputted into the image inputting section  120  from the AFE  114  at the time of image capturing, and from a CODEC  130  (described later) at the time of playback. Using the buffer memory  122 , the image processing section  121  performs a variety of image signal processing, such as color conversion and resolution conversion, on the image signal outputted from the image inputting section  120 . 
     The focus evaluating section  123  and the exposure evaluating section  124  respectively evaluate states of focus and exposure with respect to a plurality of regions included in the image signal obtained from the image processing section  121 . The characteristic detecting section  125  detects the number of characteristic portions included in the image, and sizes and positions thereof, from the image signal read from the buffer memory  122 . 
     In the present embodiment, a person&#39;s face portion is detected as the characteristic portion included in the image. As a method for detecting a face portion, there are methods using learning, typified by a neural network and a support vector machine. Further, there is a method of extracting a characteristic region in physical shape such as an eye or a nose from an image region by template matching. Moreover, as shown in Japanese Laid-Open Patent Publication (Kokai) No. 10-232934 and Japanese Laid-Open Patent Publication (Kokai) No. 2000-48184, there are methods of detecting an image characteristic amount of a skin color or an eye shape and analyzing the amount by means of statistical technique, or some other method. In the present invention, any one of these methods may be used. 
     Further, as shown in  FIG. 1 , the digital video camera  100  is provided with the CODEC  130 , a buffer memory  131 , a disk controller  132 , and a disk  133  as a recorder system block. 
     At the time of recording of a captured image, by control of the CPU  101 , the CODEC  130  encodes the image signal obtained from the image processing section  121  and writes it in the buffer memory  131 . The disk controller  132  stores the code data written in the buffer memory  131  on the disk  133  (storage medium such as a DVD). 
     On the contrary, at the time of playback of the recorded image, by control of the CPU  101 , the disk controller  132  writes the code data read from the disk  133  in the buffer memory  131 , and the CODEC  130  decodes the data. 
     Further, as shown in  FIG. 1 , the digital video camera  100  is provided with a drawing processing section  140 , a buffer memory  141 , an LCD controller  142 , an LCD  143 , an external output controller  144 , and an external terminal  145  as a display system block. 
     The drawing processing section  140  superimposes a signal of a letter, a graphic or the like, drawn based on a direction of the CPU  101 , on the image signal obtained from the image processing section  121 , and writes the obtained image signal in the buffer memory  141 . The LCD controller  142  outputs the image signal, read from the buffer memory  141 , into the LCD  143  to make it displayed. 
     Further, the external output controller  144  outputs the image signal read from the buffer memory  141  to an external output apparatus  151  connected to the external terminal  145  through a connection cable  150 . It is thereby possible to display the image in the external output apparatus  151 . 
     It is to be noted that the focus lens  110 , the aperture  111  and the CCD image sensor  113  function as a image pickup unit for capturing an image. 
     Further, the characteristic detecting section  125  functions as a characteristic detecting unit for detecting a characteristic portion from a captured image. The characteristic detecting section  125  receives an image signal in a predetermined cycle from a plurality of frames of image signals which constitute a moving picture, and detects a characteristic portion. 
     The focus evaluating section  123  and the exposure evaluating section  124  function as a state evaluating unit for evaluating a capturing state of a captured image. 
     The CPU  101  and the lens driver  112  function as a control unit for controlling the image pickup unit in accordance with a capturing state with respect to a characteristic portion. 
     When a plurality of characteristic portions are detected by the characteristic detecting unit, the CPU  101  as the control unit controls the image pickup unit in accordance with a capturing state prioritizing a characteristic portion being detected for a long period of time. 
     Here, in prioritizing a characteristic portion being detected for a long period of time from among a plurality of characteristic portions being detected, the CPU  101  sets a priority to each characteristic portion, including a size of each characteristic portion or/and a distance from the center of each characteristic portion to the center of the image. 
     Further, the CPU  101  controls a image pickup unit in accordance with a characteristic portion being detected for the longest period of time. 
     The focus evaluating section  123  as the state evaluating unit performs ranging on the captured image, and the lens driver  112  controls a focus of the focus lens  110 . 
     As the state evaluating unit, the exposure evaluating section  124  performs photometry on the photographed image, and the lens driver  112  controls exposure of the aperture  111 . 
     The image inputting section  120  functions as an input unit for inputting an image. 
     The characteristic detecting section  125  functions as a characteristic detecting unit for detecting a characteristic portion from the inputted image. 
     The drawing processing section  140  functions as a drawing unit for drawing an arbitrary graphic on the inputted image. 
     The CPU  101  also functions as a control unit for controlling the drawing unit so as to draw a graphic on a characteristic portion detected by the characteristic detecting unit. 
     When a plurality of characteristic portions are detected by the characteristic detecting unit, the CPU  101  controls the drawing unit so as to draw a predetermined graphic on each characteristic portion in accordance with a length of time when each characteristic portion is being detected. 
     When a plurality of characteristic portions are detected by the characteristic detecting unit, the CPU  101  controls the drawing unit so as to draw a graphic on a characteristic portion being detected for the longest period of time, the graphic being different from those with respect to the other characteristic portions. 
     The CPU  101  controls a drawing unit so as to draw a rectangular frame surrounding a characteristic portion. 
     The above descriptions will be specifically described below in a sequential manner. 
     Next described will be an operation performed in the case of image capturing with respect to a plurality of objects by use of the digital video camera  100 . 
     (First Embodiment) 
       FIG. 2  is a view showing an example of an output image of a video camera, outputted to the LCD or the external output apparatus shown in  FIG. 1 . 
     A person  210  whom a photographer (user) is going to capture and a person  220  as a passerby are in an output image  200 . It is to be noted that a point (X 0 , Y 0 ) shown in  FIG. 2  is the center of the output image  200 . This center (X 0 , Y 0 ) is not actually displayed in the output image  200 . In  FIGS. 3 ,  4  and  7  to  9  which will be described later, the center (X 0 , Y 0 ) is not shown. 
     The characteristic detecting section  125  determines a face portion of the person  210  as a characteristic portion and detects a size and position thereof. On the other hand, the characteristic detecting section  125  does not detect the person  220  here since the face portion thereof is small relative to the whole of the image. 
     An object list is stored in the RAM  102 , and the CPU  101  updates this object list based on a result of detection in the characteristic detecting section  125 . The CPU  101  obtains evaluation results of focus and exposure with respect to the face portion of the person  210  from the focus evaluating section  123  and the exposure evaluating section  124 . Based on those, the CPU  101  controls the lens driver  112  and the AFE  114  to adjust the focus and exposure (an aperture amount and a shutter speed). The CPU  101  controls the drawing processing section  140  to draw a detection frame  211  on the face portion of the person  210  and output an image signal with the frame superposed thereon. 
       FIG. 3  is a view showing an example of an output image after the lapse of a certain period of time from the time when the output image of  FIG. 2  was obtained. 
     In an output image  300  of  FIG. 3 , as compared with  FIG. 2 , the person  220  as the passerby has moved to the near side on the right, and the face portion thereof has become larger. Consequently, the characteristic detecting section  125  has newly detected a size and a position of the face portion of the person  220  in addition to those of the face portion of the person  210 . 
     The CPU  101  updates the object list and determines the person  210 , being detected for a longer period of time, as an object to be prioritized. Then, as in the case of  FIG. 2 , the CPU  101  adjusts focus and exposure based on evaluation results of the focus and exposure with respect to the face portion of the person  210 . 
     Further, the CPU  101  controls the drawing processing section  140  to draw a detection frame  311  by a solid line with respect to the face portion of the person  210  as the object to be prioritized and a detection frame  321  by a broken line with respect to the face portion of the person  220  as another object, and output an image signal with those frames superposed thereon. 
       FIG. 4  is a view showing an example of an output image after the lapse of a certain period of time from the time when the output image of  FIG. 3  was obtained. 
     As compared with  FIG. 3 , in an output image  400  of  FIG. 4 , the person  220  as the passerby further moves to the near side on the right and the face portion thereof has become larger than the face portion of the person  210 . 
     In accordance with a result of detection by the characteristic detecting section  125 , the CPU  101  updates the object list stored in the RAM  102 . Then, as in the case of  FIG. 3 , the CPU  101  determines the person  210 , being detected for a longer period of time, as the object to be prioritized, and adjusts focus and exposure based on evaluation results of the focus and exposure with respect to the face portion of the person  210 . 
     Further, as in the case of  FIG. 3 , the CPU  101  controls the drawing processing section  140  to respectively draw respective detection frames  411 ,  421  by a solid line and a broken line on the face portions of the person  210  and the person  220 , and output an image signal with those frames superposed thereon. 
       FIG. 5  is a flowchart showing a procedure of updating processing of the object list, the procedure is implemented by the digital video camera shown in  FIG. 1 . The updating processing of the object list is performed every time the characteristic detecting section  125  implements characteristic extraction with respect to a new image signal. 
     The present processing is implemented under control of the CPU  101  shown in  FIG. 1 . 
       FIG. 6  is a view showing an example of the object list stored in the RAM shown in  FIG. 1 . 
     In the object list stored in the RAM  102 , a position (x, y), a width w, and detection time t of an object are registered. “x” denotes a horizontal position, and “y” denotes a vertical position. The detection time t when a predetermined object is being detected can also be represented by the number of frames where the object was detected. It is to be noted that the characteristic detecting section  125  of the present embodiment detects the width w of a square including a characteristic portion as a size of the characteristic portion. 
     In step S 501  of  FIG. 5 , from the characteristic detecting section  125 , the CPU  101  obtains the number N of characteristic portions detected from an image signal. When a characteristic portion not checked with the object list remains in step S 502 , a size and a position of an n-th characteristic portion is obtained in step S 503  (here, 1≦n≦N, and “n” is counted up every time). 
     Subsequently, it is checked in step S 504  whether or not an element, whose size and position are close to or the same as the size and the position obtained in step S 503 , is registered in the object list. When the corresponding element is found in the object list, in step S 505 , the size and the position of the element are updated and the detection time (period) of (the time for detecting) the element is counted up. 
     When the corresponding element is not registered, in step S 506 , the element is newly registered as an element of the object list along with the size and the position thereof, and the detection time of the element is counted up. 
     When all the characteristic portions have been checked up in step S 502 , in step S 507 , the element not updated for a predetermined period of time is deleted (cleared), and the detection time of the element is cleaned to zero. The element is held for a predetermined period of time before deleted in order to prevent the element from being deleted immediately in a case where detection of a characteristic portion of an object to be captured happens to fail (accidentally or unfortunately fails) for a reason such that the object to be captured looks away or another person passes over. The present processing is then completed. 
     With such a configuration, camera control can be performed in an appropriate manner for capturing a person whom the photographer is going to capture by putting the person into an image capturing range for a longer period of time than another person. Further, on the screen of the LCD, the external output apparatus or the like, it can be easily confirmed which person the apparatus prioritizes in operating. 
     (Second Embodiment) 
     Next, a digital video camera of a second embodiment will be described. The digital video camera of the second embodiment is different from the digital video camera of the first embodiment in the method in which the CPU  101  determines an object to be prioritized. 
     An operation in the case of capturing a plurality of objects by use of the digital video camera  100  will be described. 
       FIG. 7  is a view showing an example of an output image of the digital video camera, outputted to the LCD or the external output apparatus shown in  FIG. 1 . 
     As shown in  FIG. 7 , a person  710  whom the photographer is going to capture and a person  720  walking behind the person  710  are in an output image  700 . The characteristic detecting section  125  takes a face portion of the person  710  as a characteristic and detects a size and a position of the face portion. On the other hand, the characteristic detecting section  125  does not detect a face portion of the person  720  since it is not facing the near side. 
     The CPU  101  updates the object list based on a result of detection by the characteristic detecting section  125 . The CPU  101  obtains evaluation results of focus and exposure with respect to the face portion of the person  710  from the focus evaluating section  123  and the exposure evaluating section  124 , and based on those, the CPU  101  controls the lens driver  112  and the AFE  114  to adjust the focus and exposure (an aperture amount and a shutter speed). 
     Further, the CPU  101  controls the drawing processing section  140  to draw a detection frame  711  on the face portion of the person  710  and output an image signal with the frame superposed thereon. 
       FIG. 8  is a view showing an example of an output image after the lapse of a certain period of time from the time when the output image of  FIG. 7  was obtained. 
     In an output image  800  of  FIG. 8 , as compared with  FIG. 7 , the person  720  walking behind has moved to the center backside, and the face portion is turned to face the near side, and hence the characteristic detecting section  125  has newly detected a size and a position of the face portion of the person  720  in addition to those of the face portion of the person  710 . 
     The CPU  101  updates the object list. Further, the CPU  101  determines the person  710  as an object to be prioritized from a length of the time when the person  710  is being detected, and the position and the size thereof, and adjusts focus and exposure based on evaluation results of the focus and exposure with respect to the face portion of the person  710 , as in the case of  FIG. 7 . 
     Moreover, the CPU  101  controls the drawing processing section  140  to draw a detection frame  811  by a solid line on the face portion of the person  710  as the object to be prioritized and a detection frame  821  by a broken line on the face portion of the person  720  as another object, and output an image signal with those frames superimposed thereon. 
       FIG. 9  is a view showing an example of an output image after the lapse of a certain period of time from the time when the output image of  FIG. 8  was obtained. 
     As compared with  FIG. 8 , in an output image  900  of  FIG. 9 , the person  720  who was walking behind has moves to the near side toward the photographer, and the face portion thereof has become larger than the face portion of the person  710 . 
     It is assumed here that, since the photographer is going to capture the person  720  as the principal object in place of the person  710 , the photographer keeps on capturing in the same position even when the person  720  in large size is getting into the center of the image. 
     In accordance with a result of detection by the characteristic detecting section  125 , the CPU  101  updates the object list. This time, the CPU  101  determines the person  720  as the object to be prioritized, from a length of the detection time of detecting the person  720 , and a position and a size thereof. The CPU  101  then adjusts focus and exposure based on evaluation results of the focus and exposure with respect to the face portion of the person  720 . 
     Further, the CPU  101  controls the drawing processing section  140  to respectively draw detection frames  921 ,  911  by a solid line and a broken line on the respective face portions of the person  720  and the person  710 , and output an image signal with those frames superposed thereon. 
       FIGS. 10 ,  11  and  12  are graphs respectively showing rates by scores at which a distance, a size of an object and a length of the detection time of the object are considered when the CPU  101  determines an object to be prioritized. 
     In  FIG. 10 , the horizontal axis shows a distance d between a position (x, y) of the object and the center (X 0 , Y 0 ) of the output image (cf.  FIG. 2 ), and the vertical axis shows a score p. The closer the object is located to the center of the image, the higher the score, and as the distance d gets closer to a distance Dmax as the farthest distance from the center of the image, the score abruptly becomes lower, and then becomes zero. 
     For example, the score is Pd 1  when the distance between the face image of the person  710  shown in  FIG. 9  and the center of the image is D 1 , and the score is Pd 2  when the distance between the face image of the person  720  shown in  FIG. 9  and the center of the image is D 2 . 
     In  FIG. 11 , the axis of abscissas shows a width w of the object and the axis of ordinates shows the score p. A score is given even at a width Wmin of the smallest characteristic portion detectable by the characteristic detecting section  125 , and the larger the width becomes to a width Wmax of the largest detectable characteristic portion, the higher the score becomes. 
     The score is Pw 1  when a length of one side of a square including the face image of the person  710  shown in  FIG. 9  is a width W 1 , and the score is Pw 2  when a length of one side of a square including the face image of the person  720  is a width W 2 . 
     In  FIG. 12 , the horizontal axis shows time t when the object is being detected, and the vertical axis shows the score p. The score remains zero until the time Tmin as a threshold, and the score gradually increases when the object continues to be detected after Tmin. The increase in score is suppressed as the time gets closer to the time Tmax, and when the time reaches Tmax, counting up the time with respect to the object is stopped and the score will no longer increase. 
     The score is Pt 1  when the detection time of the person  710  shown in  FIG. 9  is T 1 , and the score is Pt 2  when the detection time of the person  720  is T 2 . 
     In  FIG. 9 , since a total score (Pd 2 +Pw 2 +Pt 2 ) of the person  720  is higher than a total score (Pd 1 +Pw 1 +Pt 1 ) of the person  710 , the CPU  101  determines the person  720  as the object to be prioritized. 
     With such a configuration, when the person whom the photographer is going to capture is being captured closer to the center in larger size for a longer period of time, comprehensively judging from those elements, camera control can be performed in an appropriate manner for capturing the intended person. Further, on the screen of the LCD, the external output apparatus or the like, it can be easily confirmed which person the apparatus prioritizes in operating. 
     As thus described, according to each of the foregoing embodiments, since an object to be prioritized is determined in view of the time when a characteristic portion is being detected, it is possible to more appropriately auto-select a intended object and perform camera control. 
     The configuration of determining an object to be prioritized in view of the time when a characteristic portion is being detected is applicable not only to camera control but also to the time of playback of an image signal. For example, first, a luminance value and a state of a color signal of an object to be prioritized are evaluated. Then, it is possible to perform image processing, such as luminance correction, color correction and the like on the image signal for making the evaluated value become the optimum value, or production of an index image based on a signal of an image with the object. 
     In the case of being applied to the time of playback of the image signal, the present invention is used not exclusively to the camera, but is also applicable, for example, to a personal computer equipped with an image processing function. Further, the present invention is also applicable to a system configured of a plurality of devices (e.g. a host computer, an interface device and the like, constituting the image processing apparatus). 
     It is to be noted that, although the case of detecting a person&#39;s face as a characteristic portion of an object was described in the foregoing embodiments, the present invention is not restricted to the face but is applicable to any case so long as an object satisfying a previously set condition is to be detected. 
     Further, it is to be understood that the objective of the present invention may be also accomplished in the following manner. First, a storage medium in which a program code of software that realize the function of the embodiments describe above is stored is supplied to a system or an apparatus. Subsequently, a computer (or CPU, or MPU) of the system or the apparatus reads out and executes the program code stored in the storage medium. In this case, the program code itself read from the storage medium realizes the functions of any of the embodiments described above, and the program code and the storage medium in which the program is stored configure the present invention. 
     Moreover, the function of the embodiments describe above is realized not only by executing the program code read by the computer, but also in the following manner. Namely, an operating system (OS) running on the computer, or the like, performs part or all of actual processing based on a instructions in the program code, and the function of the embodiments describe above is realized by that processing. Examples of the storage medium for supplying the program code include a hard disk, a ROM, a RAM, a nonvolatile memory card, a CD-ROM, a CD-R, a DVD, an optical disk, an optical magnetic disk, MO and so on. Further, it is possible to use a computer network such as a LAN (local area network) or a WAN (wide area network) for supplying the program code. 
     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 modifications, equivalent structures and functions. 
     This application claims priority from Japanese Patent Application No. 2008-051930 filed Mar. 3, 2008, which is hereby incorporated by reference herein in its entirety.