Patent Publication Number: US-10769420-B2

Title: Detection device, detection method, computer program product, and information processing system

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2015-171005, filed on Aug. 31, 2015; the entire contents of which are incorporated herein by reference. 
     FIELD 
     Embodiments described herein relate generally to a detection device, a detection method, a computer program product, and an information processing system. 
     BACKGROUND 
     Pedestrians crossing a road at a place not defined as a safety zone such as a crosswalk accounts for a large percentage of pedestrians getting into a traffic accident. When driving on a road near the safety zone, drivers empirically pay attention to pedestrians. However, when driving on a road not defined as a safety zone, the drivers generally do not consciously pay attention to the pedestrians, and thus, the drivers unlikely respond to a pedestrian suddenly appearing and crossing a road at a place not defined as a safety zone. Therefore, a technology has been proposed which uses an image captured by an on-vehicle camera to record a case likely to lead to an accident during driving a vehicle. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating an exemplary hardware configuration of a detection device applied commonly to embodiments; 
         FIG. 2  is a diagram illustrating an example of a captured image captured by a camera according to embodiments; 
         FIG. 3  is an exemplary functional block diagram illustrating a function of a detection device according to a first embodiment; 
         FIG. 4  is an exemplary flowchart illustrating a detection process according to the first embodiment; 
         FIG. 5  is an exemplary flowchart illustrating a process of detecting a person, according to the first embodiment; 
         FIG. 6  is a diagram illustrating a distance calculation method using an installation attitude of one camera, according to the first embodiment; 
         FIGS. 7A, 7B, and 7C  are diagrams illustrating exemplary shapes of pedestrian existence ranges according to the first embodiment, on a two-dimensional map; 
         FIG. 8  is an exemplary flowchart illustrating processing of changing the size of a pedestrian existence range based on a distance relationship between a mark and a pedestrian, according to the first embodiment; 
         FIG. 9  is an exemplary functional block diagram illustrating a function of a detection device according to a modification of the first embodiment; 
         FIG. 10  is an exemplary functional block diagram illustrating function of a detection device according to a second embodiment; 
         FIG. 11  is an exemplary flowchart illustrating a detection process according to the second embodiment; 
         FIG. 12  is a diagram illustrating a positional relationship between a pedestrian and a stopped vehicle in a captured image; 
         FIGS. 13A and 13B  are diagrams illustrating positional relationships between a pedestrian and a stopped vehicle in captured images; 
         FIG. 14  is a diagram illustrating an exemplary configuration of an information processing system according to a third embodiment; 
         FIG. 15  is an exemplary functional block diagram illustrating a function of a detection device according to the third embodiment; 
         FIG. 16  is an exemplary functional block diagram illustrating a function of a server device according to the third embodiment; 
         FIG. 17  is an exemplary flowchart illustrating a process in the detection device according to the third embodiment; and 
         FIG. 18  is a diagram illustrating an example of a pedestrian existence range displayed on the detection device, according to the third embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     According to an embodiment, a detection device includes a camera, a memory, and processor circuitry. The camera is connected to an internal bus and configured to acquire an image including an area in which a mobile body is movable. The memory is connected to the internal bus and configured to store data and a program. The processor circuitry is connected to the internal bus and configured to detect at least the area, a mark on the area, and a person, from the image, calculate a first distance between the person and a position of the device when the person is in the area, and set a range according to a result of the detection and the first distance. 
     A detection device, a detection method, a detection program, and an information processing system according to an embodiment will be described below. 
     The detection device, the detection method, the detection program, and the information processing system according to an embodiment, for example, detect a road as a movement area of a vehicle, and a pedestrian being a person crossing a road, from an image captured by an on-vehicle camera mounted on the vehicle, and set a pedestrian existence range in which a pedestrian is expected to be in future, according to a position at which the pedestrian is detected. When the pedestrian existence range is used, a driver can pay attention to a pedestrian crossing a road at a place not defined as a safety zone such as a crosswalk. 
       FIG. 1  illustrates an exemplary hardware configuration of the detection device applied commonly to embodiments. In  FIG. 1 , as detection device  10  includes a central processing unit (CPU)  101 , a read only memory (ROM)  102 , a random access memory (RAM)  103 , a storage  104 , an input-output I/F  105 , a communication I/F  106 , a display controller  107 , a position acquisition device  108 , and a camera I/F  109 , and the units are connected by a bus  100  to be communicated with each other. 
     The CPU  101  operates the RAM  103  as a work memory according to programs previously stored in the ROM  102  or the storage  104 , and wholly controls the operation of the detection device  10 . That is, a computer including the CPU  101  is mounted on the detection device  10 . The storage  104  represents a hard disk drive or a non-volatile semiconductor memory (flash memory), and programs for operation of the CPU  101  or various data are stored therein. 
     The input-output I/F  105  includes for example a universal serial bus (USB), and is an interface for performing transmission and reception of data with an external device. An input device such as a keyboard or a pointing device (mouse or the like) can be connected to the input-output I/F  105 . Further, a drive device performing reading or the like of a disk recording medium such as a compact disk (CD) or a digital versatile disk (DVD) may be connected to the input-output I/F  105 . The display controller  107  converts a display control signal to a display signal, and outputs the display signal. The display control signal is generated by the CPU  101  according to a program, and the display signal is displayed on a display  120  using a liquid crystal display (LCD) or the like as a display device. 
     The communication I/F  106  controls communication with respect to a network such as a local area network (LAN) or the Internet. 
     The position acquisition device  108  acquires positional information indicating a current position. The positional information is expressed using for example latitude and longitude. The positional information may further include altitude. The position acquisition device  108  uses for example a global navigation satellite system (GNSS) to obtain a current position. The position acquisition device  108  is not limited to this configuration, and the position acquisition device  108  may use a localization system using a positional information system using a wireless LAN or an on-vehicle sensor to acquire the current position. 
     A camera  110  performs imaging according to control of the camera I/F  109 , and outputs an image signal. The camera I/F  109  controls the camera  110  according to a command from the CPU  101 , captures the image signal output from the camera  110 , and outputs the image signal as a captured image. 
     The camera  110  is mounted, for example, on a vehicle, and is installed to provide the captured image including the movement area in which the vehicle is allowed to travel, in a traveling direction of the vehicle.  FIG. 2  illustrates an example of the captured image captured by the camera  110 , according to embodiments. In  FIG. 2 , a captured image  200  includes for example an image of a movement area  201  being a road on which the vehicle travels. Further, in an example of  FIG. 2 , the captured image  200  includes images of a mark  202  being a mark on the movement area  201 , a person  203  crossing the movement area  201 , and another vehicle  204  on the movement area  201 . Note that in an example of  FIG. 2 , the mark  202  shows a crosswalk. 
     The camera  110  is not limited to a camera imaging light in the visible light region, and may employ an infrared camera capable of imaging light in the infrared region, or an ultraviolet camera capable of imaging light in the ultraviolet region. Further, in  FIG. 1 , although the detection device  10  is illustrated to be connected to one camera  110 , the configuration is not limited to this example. For example, a plurality of cameras  110  may be connected to the detection device  10  so that the cameras  110  may be installed to be directed in different directions, for example, ahead, behind, and aside the vehicle. In the follows, one camera  110  is connected to the detection device  10 , the one camera  110  being installed to image a traveling direction of the vehicle. 
     First Embodiment 
     A first embodiment will be described.  FIG. 3  is an exemplary functional block diagram illustrating a function of a detection device according to a first embodiment. In  FIG. 3 , a detection device  10   a  includes an image acquirer  11 , a detector  12 , a calculator  13 , a setting controller  14 , and a display controller  15 . The image acquirer  11 , the detector  12 , the calculator  13 , the setting controller  14 , and the display controller  15  are achieved by a detection program executed on the CPU  101 . The units are not limited to this configuration, and some or all of the image acquirer  11 , the detector  12 , the calculator  13 , the setting controller  14 , and the display controller  15  may include hardware circuits operated in cooperation with each other. 
     The image acquirer  11  acquires the captured image captured by the camera  110 . The detector  12  detects at least an image of the person  203 , an image of the movement area  201 , and an image of the mark  202  on the movement area  201 , from the captured image acquired by the image acquirer  11 . Hereinafter, “acquire the image of the person  203 ” will be appropriately referred to as, for example, “acquire the person  203 ”. 
     When the person  203  and the movement area  201  are detected by the detector  12 , and the detected person  203  is determined to be on the movement area  201 , the calculator  13  defines the detected person  203  as the pedestrian, and calculates a pedestrian distance being a distance from the vehicle to the pedestrian, based on the captured image. The setting controller  14  uses a result of the detection performed by the detector  12  and the pedestrian distance calculated by the calculator  13  to set the pedestrian existence range in which a pedestrian seems to be. 
     The display controller  15  causes the display  120  to display the pedestrian existence range set by the setting controller  14 . For example, the display controller  15  can cause the display  120  to display the captured image  200  so that the pedestrian existence range overlaps on the captured image  200 . The display controller  15  is not limited to this configuration, and the display controller  15  may cause the display  120  to display a map including the current position and display the pedestrian existence range on this map, based on the current position acquired by the position acquisition device  108 . 
       FIG. 4  is an exemplary flowchart illustrating a detection process according to the first embodiment. In step S 100 , the image acquirer  11  acquires the captured image captured by the camera  110 . In step S 100 , when the captured image is acquired by the image acquirer  11 , the process proceeds to steps S 101  and S 102 . 
     In step S 101 , the detector  12  detects the person  203  from the captured image acquired in step S 100 . Further, in step S 102 , the detector  12  acquires the movement area  201  from the captured image acquired in step S 100 . When the person  203  and the movement area  201  are detected in steps S 101  and S 102 , the process proceeds to step S 103 . 
     Although processing of steps S 101  and S 102  are parallelly performed in  FIG. 4 , the processing is not limited to this example, and processing of steps S 101  and S 102  may be sequentially performed. In this configuration, steps S 101  and S 102  may have an arbitrary order between them. 
     In step S 103 , when both of the person  203  and the movement area  201  are detected in steps S 101  and S 102 , the calculator  13  determines whether the person  203  is on the movement area  201 . When the calculator  13  determines that the person  203  is on the movement area  201 , the person  203  is defined as the pedestrian (step S 103 , Yes), and the process proceeds to step S 104 . 
     In contrast, in step S 103 , when at least one of the person  203  and the movement area  201  is not detected in steps S 101  and S 102  or when the person  203  and the movement area  201  are detected in steps S 101  and S 102  and the detected person  203  is out of the movement area  201  (step S 103 , No), the calculator  13  finishes a sequential process in the flowchart of  FIG. 4 . 
     In step S 104 , the calculator  13  calculates a distance from the vehicle (camera  110 ) to the pedestrian (person  203 ), based on the captured image  200  and an installation angle of the camera  110  relative to a horizontal direction. In the next step S 105 , the setting controller  14  uses the distance to the pedestrian calculated in step S 104  to set the pedestrian existence range being a range in which the pedestrian seems to be. The set pedestrian existence range can be displayed on the display  120  for example with the captured image  200 . 
     Next, the above processing of each step in the flowchart of  FIG. 4  will be described further in detail. First, description will be made of a process of detecting the image of the person  203  included in the captured image  200 , performed by the detector  12 , in step S 101 . Evaluation value representing the likelihood of the person is calculated for detection of the person  203 , and when the evaluation value is not less than a set threshold, existence of a person is determined. 
       FIG. 5  is an exemplary flowchart illustrating a process of detecting the person  203  by the detector  12 , according to the first embodiment. In step S 1010 , the detector  12  sets a detection range for person detection in the captured image  200  acquired in step S 100 . The detection range may be for example the whole of the captured image  200 , or part of the captured image  200 . For example, an area of the captured image  200  excluding the upper and lower end parts thereof can be set as the detection range. Further, a mask image may be prepared so that the mask image specifies a set area. The detector  12  sets a detection window at a predetermined position in the detection range. Size and shape of the detection window are not especially limited. Description will be made below on condition that the detection window has a rectangular shape. 
     In the next step S 1011 , the detector  12  determines whether processing in the detection range is finished. When the detector  12  determines that the processing in the detection range is finished (step S 1011 , Yes), a sequential process according to the flowchart of  FIG. 5  is finished. When the detector  12  determines that the processing in the detection range is not finished (step S 1011 , No), the process proceeds to step S 1012 . 
     In step S 1012 , the detector  12  calculates features in an area of the detection window set in the captured image  200 . The detector  12  can use for example histograms of oriented gradients (HOG) features, as the features. In step S 1013 , the detector  12  uses a discriminator to calculate the evaluation value representing the likelihood of the person, based on the features calculated in step S 1012 . The detector  12  can use, for example, a support vector machine (SVM) as the discriminator. 
     In the next step S 1014 , the detector  12  determines whether the evaluation value calculated in step S 1013  is not less than the threshold set previously. When the detector  12  determines that the evaluation value is less than the threshold (step S 1014 , No), the process proceeds to step S 1016 . 
     In contrast, when the detector  12  determines that the evaluation value is not less than the threshold in step S 1014  (step S 1014 , Yes), the process proceeds to step S 1015 , and the detector  12  determines that the person  203  is included in the detection window. Specifically, for example, a technology is used to detect a position to be detected. The technology is disclosed in Tomoki Watanabe, Satoshi Ito and Kentaro Yokoi: “Co-occurrence Histograms of Oriented Gradients for Human Detection”, IPSJ Transactions on Computer Vision and Applications, Vol. 2, pp. 39-47. (2010). After the processing of step S 1015 , the process proceeds to step S 1016 . 
     In step S 1016 , the detector  12  moves the detection window, and the process returns to step S 1011 . 
     Next, description will be made of a process of detecting the image of the movement area  201  included in the captured image  200 , performed by the detector  12 , in step S 102  in the flowchart of  FIG. 4 . For detection of the movement area  201 , the detector  12  previously acquires, for example, an installation attitude of the camera  110 , and when a road surface (movement area  201 ) is assumed to have a constant width, an area in which the road surface is shown can be calculated based on the installation attitude. The installation attitude includes for example, a depression angle of the camera  110 , an angle between an imaging direction of the camera  110  and the traveling direction of the vehicle, and an installation height of the camera  110 . The detector  12  is not limited to this configuration, and the detector  12  may previously set an area including the movement area  201  in the captured image  200  based on an installation position of the camera  110 , detect a straight line in the set area by Hough transform or the like, and detect, as the movement area  201 , an area surrounded by two straight lines passing near a vanishing point. 
     Next, description will be made of a process of determining whether the person  203  is in the movement area  201 , performed by the calculator  13 , in step S 103  in the flowchart of  FIG. 4 . The calculator  13  uses the person  203  and the movement area  201  detected by the detector  12  in steps S 101  and S 102  to determine whether the person  203  is in the movement area  201 . When existence of the person  203  is determined, the person  203  is defined as the pedestrian. 
     For example, the calculator  13  can determine whether the person  203  is in the movement area  201 , based on whether a lower end of the detection window is included in the movement area  201 . The detection window is determined to include the person  203  by the detector  12 , in step S 1015  in the flowchart of  FIG. 5 . In this example, when the lower end of the detection window is included in the movement area  201 , the person  203  can be determined to be in the movement area  201 . 
     Further, for example, in the detection window determined to include the person  203  in step S 1015 , a foot area of the person  203  is further detected, and the person  203  can be determined whether to be in the movement area  201 , based on whether the detected foot area is included in the movement area  201 . In this example, when the foot area is included in the movement area  201 , the person  203  can be determined to be in the movement area  201 . 
     For detection of the foot area, the above method described in person detection can be used. For example, the detector  12  obtains features of the captured image  200 , and uses the discriminator to calculate an evaluation value representing the likelihood of the foot area, based on the obtained features. The evaluation value is determined using a threshold to detect the foot area. 
     Next, description will be made of a process of calculating a distance between the person  203  and the vehicle (camera  110 ) performed by the calculator  13 , in step S 104  in the flowchart of  FIG. 4 . For example, when two or more cameras  110  are mounted to the vehicle, the distance between the camera  110  and the pedestrian (person  203 ) can be readily obtained by a stereo method. 
     When one camera  110  is mounted to the vehicle, the installation attitude of the camera  110  is used to calculate the distance between the camera  110  and the pedestrian, based on foot position information representing a position of the foot area of the pedestrian on the captured image  200 . 
     A distance calculation method using the installation attitude of one camera  110 , according to the first embodiment, will be described, using  FIG. 6 . In  FIG. 6 , the camera  110  having a focal distance f should be assumed to be installed at a position having a height h from a road surface  500  to have a depression angle θ of the imaging direction  503 . A straight line  502  perpendicularly intersecting the imaging direction  503  at a position corresponding to the focal distance f represents the captured image  200  virtually captured by the camera  110 . Further a value p represents a position of the foot area of a person  501  relative to the center of the captured image  200 , that is, an intersection point between the imaging direction  503  and the straight line  502 . 
     In this configuration, a distance d between the foot area of the person  501  and a position at which the perpendicular line from the camera  110  intersects the road surface  500  can be calculated by Equation (1). 
     
       
         
           
             
               
                 
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     Next, description will be made of a process of setting the pedestrian existence range performed by the setting controller  14 , in step S 105  in the flowchart of  FIG. 4 . In step S 105 , the setting controller  14  sets the range in which the pedestrian seems to be, based on a result of detection by the detector  12 , and the distance d between the camera  110  and the pedestrian (person  203 ) calculated by the calculator  13 . That is, the setting controller  14  sets the pedestrian existence range being a range in which the same or different pedestrian seems to be, not at time when pedestrian is monitored but at subsequent time. 
     As described above, a range in which the pedestrian may be in future can be set and stored to previously call the driver&#39;s attention before actual detection of the pedestrian, after time when the pedestrian is detected. 
     First, the setting controller  14  sets a range having a predetermined size, around the position at which the pedestrian is detected, and the range is defined as the pedestrian existence range. The position at which the pedestrian is detected is, for example, a position corresponding to the distance d calculated in the above-mentioned step S 104 , the position being in the imaging direction of the camera  110  on a horizontal plane, from the position of the camera  110 . 
       FIGS. 7A, 7B, and 7C  are diagrams illustrating exemplary shapes of pedestrian existence ranges according to the first embodiment, on a two-dimensional map.  FIG. 7A  illustrates an example of a pedestrian existence range  211   a  set into a circular shape having a predetermined radius, around a pedestrian detection position  210 .  FIG. 7B  illustrates an example of a pedestrian existence range  211   b  set into a rectangle (square in this example) having a side of predetermined length, around the pedestrian detection position  210 . Further,  FIG. 7C  illustrates an example of a pedestrian existence range  211   c  set along the shape of a road  212 , around the pedestrian detection position  210 . 
     In terms of size of the pedestrian existence range, for example, the pedestrian existence range  211   a  having a circular shape of  FIG. 7A  may have a radius being several times larger than the width of the road. For example, when the width of the road is 10 meters, the radius of the pedestrian existence range  211   a  may be several ten meters (e.g., approximately 20 meters to 30 meters). 
     Further, in the first embodiment, the size of the pedestrian existence range is changed according to a result of detection by the detector  12 . As an example, the size of the pedestrian existence range can be changed based on a distance relationship between the mark  202  (crosswalk) and the pedestrian which are detected from the captured image  200 . 
     An exemplary process of changing the size of the pedestrian existence range based on the distance relationship between the mark  202  and the pedestrian, according to the first embodiment will be described, using a flowchart of  FIG. 8 . In step S 1051 , the detector  12  detects for example a crosswalk area from the movement area  201 , as one of the mark  202 . 
     The detector  12  can use, as a method of detecting the crosswalk area, for example the method having been described in person detection. For example, the detector  12  obtains features of the captured image, and uses the discriminator to calculate an evaluation value representing the likelihood of the crosswalk, based on the obtained features. The evaluation value is determined using a threshold to detect the crosswalk area. The features are not limited to the HOG feature, and Gabor features can be used as features effectively using a brightness difference. 
     In step S 1052 , the detector  12  determines whether the crosswalk area is successfully detected. When the crosswalk area is determined to be successfully detected (step S 1052 , Yes), the process proceeds to step S 1053 . In contrast, when the detection of the crosswalk area results in failure (step S 1052 , No), a sequential process in the flowchart of  FIG. 8  is finished. 
     In step S 1053 , the calculator  13  calculates a distance from the camera  110  to the crosswalk area detected in step S 1052 . The mark  202  exists on the road surface, that is, on the movement area  201 , and thus the distance can be calculated using Equation (1). In the next step S 1054 , the calculator  13  calculates a distance D between the mark  202  and the pedestrian (person  203 ), based on the distance calculated in step S 104  in the flowchart of  FIG. 4 , and the distance to the crosswalk area calculated in step S 1053 . 
     In the next step S 1055 , the setting controller  14  determines whether the distance D calculated in step S 1054  is less than a threshold. When the setting controller  14  determines that the distance D is not less than the threshold (step S 1055 , No), the sequential process according to the flowchart of  FIG. 8  is finished. In contrast, in step S 1055 , when the setting controller  14  determines that the distance D is less than the threshold (step S 1055 , Yes), the process proceeds to step S 1056 . 
     In step S 1056 , the setting controller  14  adjusts the size of the pedestrian existence range according to a value of the distance D. In the first embodiment, the setting controller  14  reduces the pedestrian existence range at a constant rate. 
     For example, the setting controller  14  adjusts the distance D and the size of the pedestrian existence range to be inversely proportional. In this configuration, in the case of the pedestrian existence range  211   a  having a circular shape of  FIG. 7A , the distance D and the radius of the pedestrian existence range  211   a  may be adjusted inversely to each other. The setting controller  14  is not limited to this configuration, and the setting controller  14  may adjust the size of the pedestrian existence range to be inversely proportional to the square of the distance D. Further, when the distance D is not less than the threshold, the setting controller  14  may increase the pedestrian existence range according to the distance D. 
     As described above, according to the first embodiment, when the pedestrian crossing the road at a place other than the crosswalk is detected in the road on which the vehicle travels, the pedestrian existence range having a predetermined size is set to the position of the detected pedestrian. When the pedestrian existence range set as described above is used, the range in which the pedestrian may be can be shown to the driver, and the driver&#39;s attention can be drawn. 
     Modification of First Embodiment 
     A modification of the first embodiment will be described.  FIG. 9  is an exemplary functional block diagram illustrating a function of a detection device according to the modification of the first embodiment Note that in  FIG. 9 , parts common to those having been illustrated in  FIG. 3  are denoted by the same reference signs, and detailed description thereof will be omitted. 
     In  FIG. 9 , a detection device  10   a ′ additionally includes a positional information acquirer  16 , compared with the detection device  10   a  illustrated in  FIG. 3 . The positional information acquirer  16  uses the position acquisition device  108  to acquire the current position. The positional information acquirer  16  transmits acquired positional information to the setting controller  14 . Further, the positional information acquirer  16  acquires a position at which the captured image is acquired, according to a captured-image acquisition notification from the image acquirer  11 , and transmits positional information indicating the position to the setting controller  14 . For example, the setting controller  14  adds the positional information transmitted from the positional information acquirer  16  to the set pedestrian existence range, and can cause the display controller  15  to display the pedestrian existence range on the two-dimensional map, as illustrated in  FIGS. 7A to 7C . 
     Further, information about the set pedestrian existence range can be stored for example in the storage  104  in association with the positional information. In this configuration, when the vehicle travels at a position near the stored positional information, even if a pedestrian is not actually detected at that time, the pedestrian existence range can be shown to the driver in consideration of the probability of existence of a pedestrian. Therefore, the driver&#39;s attention can be drawn. 
     Second Embodiment 
     Next, a second embodiment will be described.  FIG. 10  is an exemplary functional block diagram illustrating function of a detection device according to the second embodiment. Note that in  FIG. 10 , parts common to those having been illustrated in  FIG. 3  are denoted by the same reference signs, and detailed description thereof will be omitted. 
     In  FIG. 10 , a detection device  10   b  additionally includes an age estimator  21  and a stopped-vehicle recognizer  22 , compared with the detection device  10   a  illustrated in  FIG. 3 . The age estimator  21  recognizes attribute information of the pedestrian obtained by the calculator  13  in step S 103  of  FIG. 4 , based on an image of the pedestrian in the captured image  200 , and estimates the age of the pedestrian based on the recognized attribute information. Further, in the detection device  10   b , the detector  12  further detects the other vehicle  204  being in the movement area  201  from the captured image  200  acquired by the image acquirer  11 . The stopped-vehicle recognizer  22  recognizes whether the other vehicle  204  detected by the detector  12  stops. 
     The setting controller  14  changes the size of the set pedestrian existence range according to the age of the pedestrian estimated by the age estimator  21 . Further, the setting controller  14  obtains a positional relationship between the other vehicle  204  recognized by the stopped-vehicle recognizer  22 , and the pedestrian obtained by the calculator  13 , and changes the size of the pedestrian existence range according to the obtained positional relationship. 
       FIG. 11  is an exemplary flowchart illustrating a detection process according to the second embodiment. Note that the flowchart of  FIG. 11  is performed after setting the pedestrian existence range by processing of step S 105  in the flowchart of  FIG. 4 . 
     In step S 201 , the age estimator  21  recognizes attribute information of the pedestrian obtained by the calculator  13  based on the image of the pedestrian, and estimates the age of the pedestrian based on the recognized attribute information. In the next step S 202 , the stopped-vehicle recognizer  22  recognizes whether the other vehicle  204  detected by the detector  12  is a stopped vehicle. Note that processing of steps S 201  and S 202  may be exchanged in the order or may be performed in parallel. 
     In the next step S 203 , the setting controller  14  determines whether the age estimated by the age estimator  21  in step S 201  is out of a predetermined age range. When the setting controller  14  determines that the estimated age is within the predetermined age range (step S 203 , No), the process proceeds to step S 205 . In contrast, when the setting controller  14  determines that the estimated age is out of the predetermined age range (step S 203 , Yes), the process proceeds to step S 204 . 
     In step S 204 , the setting controller  14  increases the pedestrian existence range set in step S 105  in the flowchart of  FIG. 4 . Then, the process proceeds to step S 205 . 
     Determination process of step S 203  determines whether the pedestrian is an older person or a younger person, and the predetermined age range is set, for example, to a range not less than ten-years old and less than 60-years old. In this condition, when the estimated age is less than ten-years old or not less than 60-years old, the estimated age is determined to be out of the predetermined age range, the process proceeds to step S 204 , and the pedestrian existence range is increased. The older person or the younger person is considered to be slow in action (e.g., older person and younger person), or considered to be unstable in action (e.g., younger person), compared with those of the other ages (defined as general adult). Therefore, when the pedestrian is considered to be the older person or the younger person, the pedestrian existence range is increased in step S 204 , and the effect of drawing the driver&#39;s attention is increased. 
     In step S 205 , the stopped-vehicle recognizer  22  determines whether the other vehicle  204  detected by the detector  12  is stopped, according to a result of the recognition in step S 202 . When the stopped-vehicle recognizer  22  determines that the other vehicle  204  is not stopped, that is, the other vehicle  204  moves (step S 205 , No), a sequential process according to the flowchart of  FIG. 11  is finished. In contrast, when the stopped-vehicle recognizer  22  determines that the detected other vehicle  204  is stopped (step S 205 , Yes), the process proceeds to step S 206 . 
     In step S 206 , the setting controller  14  adjusts the size of the pedestrian existence range, based on a positional relationship between the pedestrian and the other vehicle  204  recognized to be stopped on the captured image  200 . Then, the sequential process according to the flowchart of  FIG. 11  is finished. 
     Next, description will be made of an age estimation process performed by the age estimator  21 , in step S 201 . The age estimator  21  recognizes, based on the image of the pedestrian, the attribute information about the pedestrian detected by the detector  12 . As the attribute information about the pedestrian, for example, the pedestrian&#39;s gender, skin color, height, clothing, personal effects, and physical features can be considered. The age estimator  21  estimates the age of the pedestrian, based on the recognized attribute information about the pedestrian. For example, the age estimator  21  can estimate age based on height of the attribute information about the pedestrian. In this configuration, when the height of the pedestrian is not more than a predetermined value, the pedestrian may be considered to be the older person or the younger person. 
     The height of the pedestrian can be recognized, applying the method of calculating the distance from the camera  110  to the pedestrian, performed by the calculator  13  in step S 104  of  FIG. 4 . For example, the foot area and a head area of the pedestrian are recognized from the image of the pedestrian, and the height is recognized based on positions of the recognized foot area and head area in the captured image  200 , and a distance to the foot area of the pedestrian. As an example, a threshold of height is set, and height in the captured image  200  (number of pixels) corresponding to a threshold height is previously obtained for each distance. The height of the pedestrian can be calculated based on height from the foot area to the head area of the pedestrian, and the distance. 
     The age estimation process is not limited to this configuration, and the pedestrian&#39;s age can be also estimated based on a movement speed of the pedestrian. In this configuration, when the pedestrian is tracked in time series to obtain his/her movement speed, and the obtained movement speed is not more than a set threshold, the pedestrian may be determined to be an older person or a younger person. 
     Next, description will be made of a process of recognizing the stopped vehicle performed by the stopped-vehicle recognizer  22 , in step S 202 . The stopped-vehicle recognizer  22  traces the other vehicle  204  detected by the detector  12  in time series, and determines, based on an amount of movement thereof, whether the other vehicle  204  moves or is stopped. Similarly to the processing of step S 104  in the flowchart of  FIG. 4 , a distance from the camera  110  to the other vehicle  204  can be calculated, based on a lower end area of the other vehicle  204 . Thus, the other vehicle  204  is traced in time series to sequentially obtain distances to the other vehicle  204  in time series, and the speed of the other vehicle  204  relative to the vehicle can be calculated. The calculated speed may be employed as the amount of movement. 
     Next, description will be made of a process according to the positional relationship between the other vehicle  204  and the pedestrian on the captured image  200 , in step S 206 . When the stopped-vehicle recognizer  22  recognizes that the other vehicle  204  is stopped, the setting controller  14  adjusts the size of the pedestrian existence range according to a distance between the stopped other vehicle  204  and the pedestrian. The distance between the stopped other vehicle  204  and the pedestrian may be a distance on the captured image  200 , or may be actual distances of the other vehicle  204  and the pedestrian which are calculated, as described above. 
     The setting controller  14  uses, for example, a foot position of the pedestrian and a lower end position of a stopped vehicle area, on the captured image  200 , and obtains a positional relationship between the pedestrian and the stopped vehicle in the captured image  200 . 
     The positional relationship between the pedestrian and the stopped vehicle in the captured image  200  will be described, using  FIGS. 12 and 13 . As illustrated in  FIG. 12 , a difference in horizontal coordinate value in the captured image  200  is defined as a width Δw, and a difference in vertical coordinate value therein is defined as a height Δh, between the foot position  220  of the detected pedestrian (person  203 ) and the lower end position  221  of the stopped vehicle (other vehicle  204 ), in the captured image  200 . Further, the setting controller  14  sets thresholds for the width Δw and the height Δh. 
       FIG. 13A  illustrates an example of the width Δw not less than the threshold. Further,  FIG. 13B  illustrates an example of the height Δh not less than the threshold. When the width Δw and the height Δh are not more than the thresholds, respectively, the setting controller  14  determines that the distance between the other vehicle  204  and the pedestrian is small in an actual space. In this condition, the setting controller  14  for example increases the pedestrian existence range. Further, for example, when the width Δw and the height Δh are not less than the thresholds, respectively, the setting controller  14  determines that the distance between the other vehicle  204  and the pedestrian is large in the actual space. In this condition, the setting controller  14  for example reduces the pedestrian existence range. Otherwise, the setting controller  14  does not adjust the pedestrian existence range in step S 206 . 
     Note that the above method of determining the positional relationship between the pedestrian and the stopped vehicle is not limited to the above-mentioned example. For example, when at least one of the height Δh and the width Δw is not less than the threshold, the distance between the other vehicle  204  and the pedestrian may be determined to be large. 
     As described above, in the second embodiment, the pedestrian existence range set according to the process of the first embodiment is further adjusted based on the attribute information about the pedestrian or the distance between the pedestrian and the stopped vehicle. Therefore, the driver&#39;s attention can be further accurately drawn. 
     Third Embodiment 
     Next, a third embodiment will be described.  FIG. 14  illustrates an exemplary configuration of an information processing system according to the third embodiment. In  FIG. 14 , the information processing system includes a server device  60  including a database (DB)  61 , and one or more detection devices  10   c ,  10   c , and . . . are connected to a network  51  by wireless communication to perform communication with the server device  60  through the network  51 . An AP  50  is a relay device for connecting the detection devices  10   c ,  10   c , and . . . to the network  51  by wireless communication. Although wireless communication performed by each detection device  10   c  is not limited in communication method as long as data communication is allowed with a predetermined communication party, a wireless local area network (LAN) can be employed. 
     In the third embodiment, in such a configuration, each detection device  10   c  associates the information about the set pedestrian existence range with the positional information indicating the position at which the pedestrian existence range is set, and stores the information in the RAM  103  or the storage  104 . When another set of a pedestrian existence range and positional information is acquired, after a set of a pedestrian existence range and positional information has been stored, each detection device  10   c  determines whether the acquired positional information is included in the stored pedestrian existence range. 
     Further, each detection device  10   c  transmits the set of the information about the pedestrian existence range and the positional information stored in the RAM  103  or the storage  104  to the server device  60 . The server device  60  cumulatively stores, in the DB  61 , the set of the information about the pedestrian existence range and the positional information transmitted from each detection device  10   c . Further, the server device  60  transmits the set of the information about the pedestrian existence range and the positional information stored in the DB  61  to each detection device  10   c.    
     Therefore, the driver of the vehicle on which the detection device  10   c  is mounted can know, for example, the pedestrian existence range in a position where the vehicle has not been traveled in the past, and the driver can pay attention to even a place where the vehicle has not traveled. 
       FIG. 15  is an exemplary functional block diagram illustrating a function of the detection device  10   c  according to the third embodiment. Note that in  FIG. 15 , parts common to those having been illustrated in  FIG. 9  are denoted by the same reference signs, and detailed description thereof will be omitted. 
     In  FIG. 15 , the detection device  10   c  additionally includes a storage  31 , a transmitter  32 , and a receiver  33 , compared with the detection device  10   a ′ illustrated in  FIG. 9 . The storage  31  controls writing and reading to the RAM  103  or the storage  104  to store and read information. The transmitter  32  transmits the information stored in the storage  31  by wireless communication. The receiver  33  receives information transmitted by wireless communication, and transmits the information to the storage  31 . 
     Note that the age estimator  21  and the stopped-vehicle recognizer  22  illustrated in  FIG. 10  may be added to the configuration of  FIG. 15  to adjust the set pedestrian existence range, based on an estimated age of the pedestrian, the positional relationship between the pedestrian and the stopped vehicle, or the like. 
       FIG. 16  is an exemplary functional block diagram illustrating a function of the server device  60  according to the third embodiment. Note that the server device  60  can be configured as a general computer including hardware, i.e. a CPU, a ROM, a RAM, a storage, a communication I/F or the like, and detailed description thereof will be omitted. The server device  60  is not limited to a configuration of a single device, and may have for example functions distributed to a plurality of devices. 
     In  FIG. 16 , the server device  60  includes a receiver  62 , a transmitter  63 , and a storage  64 . The storage  64  controls writing and reading to the DB  61  to store and read information. The receiver  62  receives information transmitted through the network  51 , and transmits the received information to the storage  64 . The transmitter  63  transmits the information stored in the storage  64  through the network  51 . 
       FIG. 17  is an exemplary flowchart illustrating a process in the detection device  10   c  according to the third embodiment. In step S 300 , the image acquirer  11  acquires the captured image. At this time, the image acquirer  11  transmits notification of acquisition of the captured image to the positional information acquirer  16 . In the next step S 301 , the positional information acquirer  16  acquires the positional information indicating the current position, according to the notification of acquisition of the image, from the image acquirer  11 . 
     In the next step S 302 , the setting controller  14  sets the pedestrian existence range based on the captured image acquired in step S 300 . That is, as described using the flowchart of  FIG. 4 , the detector  12  detects the person  203  and the movement area  201  from the captured image acquired by the image acquirer  11  (steps S 101  and S 102  of  FIG. 4 ). When the person  203  detected by the detector  12  is on the movement area  201 , the calculator  13  defines the person  203  as the pedestrian (step S 103  of  FIG. 4 ), and calculates the distance from the camera  110  to the pedestrian, based on the captured image and the installation attitude of the camera  110  (step S 104  of  FIG. 4 ). The setting controller  14  uses the calculated distance to set the pedestrian existence range. 
     In the next step S 303 , the storage  31  associates the positional information upon imaging acquired in step S 301 , and information indicating the pedestrian existence range set in step S 302 , and stores a first set of the positional information and the pedestrian existence range. The information indicating the pedestrian existence range includes the size of the pedestrian existence range, and information indicating the position of the detected pedestrian. The position of the pedestrian can be obtained based on the current position upon imaging and the distance from the camera  110  to the pedestrian. 
     In the next step S 304 , the transmitter  32  transmits the first set of the positional information and the pedestrian existence range stored in the storage  31  to the server device  60 . Each time the first set of the positional information and the pedestrian existence range is stored in the storage  31 , the transmitter  32  can transmit the stored first set of the positional information and the pedestrian existence range. Further, the transmitter  32  may transmit a plurality of first sets of the positional information and the pedestrian existence range collectively, for example, at fixed time intervals. 
     The first set of the positional information and the pedestrian existence range transmitted from the transmitter  32  is received by the receiver  62  in the server device  60 , through the network  51 . In the server device  60 , the storage  64  cumulatively stores, as a second set, the first set of the positional information and the pedestrian existence range received by the receiver  62 , in the DB  61 . Further, when the server device  60  receives the first set of the positional information and the pedestrian existence range, from the detection device  10   c , storage  64  reads one or more second sets of the positional information and the pedestrian existence range stored in the DB  61 . The transmitter  63  transmits the second set of the positional information and the pedestrian existence range read by the storage  64 , to the detection device  10   c . The detection device  10   c  is a transmission source of the received first set of the positional information and the pedestrian existence range. The transmitter  63  can transmit the one or more second sets. 
     In step S 305  of  FIG. 17 , the detection device  10   c  waits for reception, by the receiver  33 , of communication from the server device  60 , that is, of the second set of the positional information and the pedestrian existence range transmitted from the server device  60 . When the receiver  33  does not receive communication from the server device  60 , the process returns to step S 305 , and when the receiver  33  receives the communication from the server device  60 , the process proceeds to step S 306 . 
     In step S 306 , the receiver  33  receives the second set of the positional information and the pedestrian existence range transmitted from the server device  60 . In the next step S 307 , the receiver  33  selects any of the received second sets of the positional information and the pedestrian existence range, and causes the storage  31  to cumulatively store the selected second set of the positional information and the pedestrian existence range. As a result, the storage  31  stores the first set of the positional information and the pedestrian existence range, acquired and set in the detection device  10   c , and the second set of the positional information and the pedestrian existence range, transmitted from the server device  60  and received and selected in the detection device  10   c.    
     For example, the receiver  33  can acquire the current position from the positional information acquirer  16 , select a second set of the positional information and the pedestrian existence range, the positional information having a distance not more than a fixed value to the current position, from the one or more the second sets of the positional information and the pedestrian existence range, received from the server device  60 , and causes the storage  31  to store the selected second set. Further, the receiver  33  may cause the storage  31  not to store a second set of the positional information and the pedestrian existence range, the positional information having a distance not less than the fixed value to the current position, from the one or more second sets of the positional information and the pedestrian existence range, received from the server device  60 . For example, the receiver  33  discards one or more second sets of the positional information and the pedestrian existence range not stored in the storage  31 , from the received one or more second sets of the positional information and the pedestrian existence range. 
     Further, when a new first set of the positional information and the pedestrian existence range additionally obtained and set, or a second set of the positional information and the pedestrian existence range transmitted from the server device  60 , is stored, the storage  31  may erase a predetermined number of sets of the positional information and the pedestrian existence range, older in time, from the first and the second sets of the positional information and the pedestrian existence range which have been stored. 
     Further, the server device  60  may be configured to normally transmits the second sets of the positional information and the pedestrian existence range, and the detection device  10   c  may be configured so that the receiver  33  receives, at fixed time intervals, the transmitted second sets of the positional information and the pedestrian existence range. Further, the server device  60  may be configured to select a second set of the positional information and the pedestrian existence range, the positional information having a distance not more than the fixed value to the positional information transmitted from the detection device  10   c , from the second sets of the positional information and the pedestrian existence range stored in the storage  64 , and transmit the selected second set to the detection device  10   c.    
     When the processing of step S 307  is finished, a sequential process according to the flowchart of  FIG. 17  is finished. 
     The detection device  10   c  according to the third embodiment can include a determination unit. The determination unit determines whether a current position of the vehicle on which the detection device  10   c  is mounted is included in any of one or more pedestrian existence ranges, based on the positional information acquired by the positional information acquirer  16  in step S 301  in the flowchart of  FIG. 17 , and the set of the positional information and the pedestrian existence range stored by the storage  31  in step S 307 . The determination unit transmits notification of a determination result to the driver of the vehicle. 
       FIG. 18  illustrates an example of the pedestrian existence range displayed on the display  120  of the detection device  10   c , according to the third embodiment. In an example of  FIG. 18 , a map  300  including a vehicle  301  is displayed on the display  120 . The map  300  is displayed by the display controller  15 , based on, for example, the information indicating the current position acquired by the position acquisition device  108  included in the detection device  10   c , and, for example, map information previously stored in the storage  104 . 
     In  FIG. 18 , the detection device  10   c  is configured so that the display controller  15  causes the display  120  to display, on the map  300 , the pedestrian existence range having a distance not more than a predetermined value to the position of the vehicle  301 , selected from the first and the second sets of the positional information and the pedestrian existence range, stored in the storage  31 . In an example of  FIG. 18 , three pedestrian existence ranges, that is, pedestrian existence ranges  310 ,  311 , and  312  are displayed on the map  300 , by a display method different from that of a road on the map  300 . The three pedestrian existence ranges are displayed in different display colors in this example. Based on this display, the driver of the vehicle  301  can know that a certain range in the traveling direction of the vehicle  301  is, for example, the pedestrian existence range  311 , before the vehicle  301  arrives at the pedestrian existence range  311 , and the driver can pay attention to the pedestrian. 
     Further, the number of times of storing each of the pedestrian existence ranges  310 ,  311 , and  312  by the storage  31  or the number thereof stored may be counted to further change the display method of each of the pedestrian existence ranges  310 ,  311 , and  312  according to count obtained as a result of counting. 
     An exemplary method of counting the pedestrian existence range will be described. For example, when the setting controller  14  sets the pedestrian existence range based on the captured image acquired by the image acquirer  11 , the above-mentioned determination unit acquires the positional information indicating the position at which the captured image is acquired, from the positional information acquirer  16 . The determination unit determines whether there is a set including a pedestrian existence range including the position indicated by the acquired positional information within a range in the sets of the positional information and the pedestrian existence range stored in the storage  31 . When there is the set, the determination unit increments the count of the corresponding set stored in the storage  31 . Function of the determination unit may be included, for example, in the function of the setting controller  14 . 
     In an example of  FIG. 18 , for example, a first threshold and a second threshold having a value lower than that of the first threshold are provided for the count, and according to the results of comparison between the count of each of the pedestrian existence ranges  310 ,  311 , and  312  and the first and second thresholds, the display color of each of the pedestrian existence ranges  310 ,  311 , and  312  is changed. As an example, when the result has a large count, the pedestrian existence range is considered to have a larger probability of existence of the pedestrian, and display is performed to indicate a higher risk. 
     Specifically, in  FIG. 18 , in the pedestrian existence ranges  310 ,  311 , and  312 , for example the pedestrian existence range  311  having a count larger than the first threshold has a color representing a higher risk (e.g., red), for example the pedestrian existence range  310  having a count less than the first threshold and not less than the second threshold has a color representing a medium risk (e.g., yellow), and for example the pedestrian existence range  312  having a count less than the second threshold has a color representing a lower risk (e.g., green). 
     In this configuration, the number of thresholds is not limited to two, and may be three or more or may be one. Further, the threshold may be changed according to a period of time, season, weather, or the like. For example, the threshold may be changed according to a period of time so that night has a threshold lower than that of the daytime to further draw driver&#39;s attention at night. 
     Note that the number of times of counting the pedestrian existence range or the number thereof counted may include the number of times of storing the pedestrian existence range set by the detection device  10   c  mounted to the vehicle  301  in the storage  31 , or the number thereof stored, and the number of times of storing the pedestrian existence range transmitted from the server device  60  in the storage  31 , or the number thereof stored. The number of times of counting the pedestrian existence range or the number thereof counted is not limited to this configuration, and may include only the number of times of storing the pedestrian existence range set by the detection device  10   c  mounted to the vehicle  301 , in the storage  31 , or the number thereof stored. 
     As described above, according to the count obtained as a result of counting the number of times of storing each of the pedestrian existence ranges  310  to  312  by the storage  31  or the number thereof stored, the display method of each of the pedestrian existence ranges  310 ,  311 , and  312  are changed, and the range to which the driver&#39;s attention is to be paid can be clearly shown. 
     Further, although the pedestrian existence ranges  310  to  312  are displayed on the map  300  obtained based on the positional information acquired by the positional information acquirer  16 , in the above-mentioned configuration, the configuration is not limited to this example. For example, the display controller  15  may cause the display  120  to display the pedestrian existence ranges  310  to  312  to overlap on the captured image acquired by the image acquirer  11 . 
     Other Embodiments 
     A detection program for performing a detection process according to embodiments is provided by being recorded in a computer-readable recording medium, which may be provided as a computer program product, such as a compact disk (CD) or a digital versatile disk (DVD) in an installable format file or executable format file. The detection program is not limited to this configuration, and may be provided by being stored previously in the ROM  102 . 
     Further, the detection program for performing the detection process according to embodiments may be provided by being stored on a computer connected to a communication network such as the Internet, and by being downloaded via the communication network. Further, the detection program for performing the detection process according to embodiments and a modification may be configured to be provided or distributed via the communication network such as the Internet. 
     In the first embodiment, the detection program for performing the detection process according to embodiments and a modification has, for example, a module configuration including the above-mentioned units (the image acquirer  11 , the detector  12 , the calculator  13 , the setting controller  14 , and the display controller  15 ). As actual hardware, the CPU  101  reads, for example, the detection program from the storage  104  and executes the detection program, the units are loaded on a main storage device (e.g., RAM  103 ), and the units are generated on the main storage device. 
     While certain embodiments have been described, these embodiments have been presented by way of example only, and are not intended to limit the scope of the inventions. Indeed, the novel embodiments described herein may be embodied in a variety of other forms; furthermore, various omissions, substitutions and changes in the form of the embodiments described herein may be made without departing from the spirit of the inventions. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.