Abstract:
This vehicle periphery monitoring device appropriately determines whether or not an animal detected by an imaging device is a high-risk animal which may possibly contact the vehicle. For example, compared with an animal in a posture with the head facing downwards, an animal in a posture with the head facing upwards is determined to be a high-risk animal which may suddenly bolt, so the latter animal is enclosed in a thick red frame and highlighted as a warning, and an alarm is emitted from speakers.

Description:
TECHNICAL FIELD 
     The present invention relates to a vehicle periphery monitoring apparatus (vehicle periphery monitoring device) for monitoring the periphery of a vehicle using an image captured by an infrared camera (grayscale image) mounted on the vehicle, and more particularly to a vehicle periphery monitoring apparatus which is suitable for use on a vehicle particularly when the vehicle travels at night or in dark places. 
     BACKGROUND ART 
     As disclosed in Japanese Laid-Open Patent Publication No. 2003-284057 (hereinafter referred to as “JP2003-284057A”), it has heretofore been customary for a vehicle periphery monitoring apparatus to detect an object such as a pedestrian or the like that may possibly collide with a vehicle, from images (a grayscale image and a binary image converted therefrom) of the periphery of the vehicle, which are captured by infrared cameras, and to provide information about the detected object to the driver of the vehicle. 
     More specifically, the vehicle periphery monitoring apparatus disclosed in JP2003-284057A detects, as an object, a high-temperature area in images in the periphery of the vehicle, which are captured by a set of left and right infrared cameras (stereo cameras), and calculates the distance up to the object by determining a parallax of the object in the left and right images. In addition, the vehicle periphery monitoring apparatus detects an object such as a pedestrian or the like that is likely to affect the travel of the vehicle, i.e., that may possibly collide with the vehicle, based on the direction in which the object moves and the position of the object, and issues a warning concerning the detected object (see paragraphs [0014] and [0018] of JP2003-284057A). 
     Japanese Patent No. 4267657 (hereinafter referred to as “JP4267657B”) discloses a vehicle periphery monitoring apparatus, which captures at least two images (two frames) of an object in the periphery of a vehicle at a predetermined time interval, using a single infrared camera mounted on the vehicle. If the size of a present image of the object changes from the size of a preceding image of the object, the change in size becomes greater as the relative speed between the object and the vehicle is higher. As the relative speed between the object and the vehicle is higher, an arrival time, which any object that is present in front of the vehicle takes to arrive at the vehicle, becomes shorter. Consequently, even though a single infrared camera is used, the vehicle periphery monitoring apparatus can monitor the periphery of the vehicle by estimating the arrival time from the rate of change between the sizes of images of the object that are captured at the predetermined time interval (see paragraphs [0006], [0007], and [0061] of JP4267657B). 
     Japanese Patent No. 4173901 (hereinafter referred to as “JP4173901B”) discloses a vehicle periphery monitoring apparatus, which detects animals other than people from among objects, because objects that are present in the periphery of a vehicle and that may possibly collide with the vehicle are not limited to pedestrians. Large animals such as a deer or the like may also be present on the road and may collide with the vehicle (see paragraph [0006] of JP4173901B). 
     SUMMARY OF INVENTION 
     The vehicle periphery monitoring apparatus disclosed in JP2003-284057A, which detects an object with stereo cameras and issues a warning about the detected object, is problematic in that it is highly costly since it carries two infrared cameras. 
     The vehicle periphery monitoring apparatus disclosed in JP4267657B, which uses a single infrared camera for a cost reduction, can be used to image pedestrians that move in fixed patterns along motion vectors, but is not satisfactory in terms of performance for imaging animals that move in irregular patterns not along motion vectors, because the distance accuracy is low. 
     The vehicle periphery monitoring apparatus disclosed in JP4173901B basically defects an animal from the shape of its torso based on the finding that the ratio of the horizontal width to vertical width of the torso of a quadrupedal animal can be distinguished from the ratio of the horizontal width to vertical width of the torso of a bipedal human being (see paragraphs [0005] and [0064] of JP4173901B). 
     The present invention has been made in connection with the above background-art technologies. It is an object of the present invention to provide a vehicle periphery monitoring apparatus which is capable of accurately judging at a reduced cost whether or not a detected animal is an animal that is so dangerous as to possibly affect the way in which a vehicle incorporating the vehicle periphery monitoring apparatus travels. 
     According to the present invention, there is provided a vehicle periphery monitoring apparatus for monitoring the periphery of a vehicle using an image captured by an image capturing device mounted on the vehicle, including an animal detection processor configured to detect an animal as an object to be monitored from the image, and an animal hazard degree judgment section configured to judge whether the animal is a hazardous animal which may possibly affect the travel of the vehicle or not based on a posture shape of the animal which is detected from the image. 
     According to the present invention, the animal hazard degree judgment section judges whether or not the animal is a hazardous animal which may possibly affect the travel of the vehicle, not based simply on the position of the animal, but based on the posture shape of the animal. Therefore, it is possible to accurately judge a hazardous animal, and hence to appropriately call attention of the driver to the hazardous animal. Since it is possible to judge an animal without using distance information, the processing load can be reduced, and the judgment can be performed quickly. Therefore, the vehicle periphery monitoring apparatus can use a low-rate CPU and can be reduced in cost. As described later, the present invention can be implemented even if the image capturing device is a single image capturing device. 
     The animal hazard degree judgment section may judge that the animal is a hazardous animal if legs are detected in the posture shape of the animal. An animal that is positioned on a road has its legs detected, and an animal that is positioned outside of the road does not have its legs detected because such an animal is often positioned on a tuft of grass or the like. Therefore, it is possible to judge whether an animal is positioned on the road or outside of the road by judging whether the animal shows its legs or not. 
     The animal hazard degree judgment section may judge that the animal is a hazardous animal if the angle of a neck of the animal with respect to a torso thereof is directed upwardly in the posture shape of the animal. Since an animal with the angle of its neck with respect to the torso being directed downwardly, does not jump out abruptly, it is possible to judge the animal with the angle of the neck directed upwardly as more hazardous than the animal with the angle of the neck directed downwardly. 
     The animal hazard degree judgment section may judge that the animal is a hazardous animal if the distance from the position of the animal to a road edge to which the face of the animal is directed is greater than a predetermined distance. An animal which is spaced by a longer distance from the road edge toward which the face of the animal is directed is regarded as staying on the road for a long period of time. Therefore, it is possible to judge such an animal as a hazardous animal. 
     When the animal hazard degree judgment section detects a plurality of candidates for hazardous animals from the image, the animal hazard degree judgment section may judge one of the detected candidates for the hazardous animals which contacts a road surface at a position that is closest to the vehicle, as a hazardous animal. 
     When the animal hazard degree judgment section detects a plurality of candidates for hazardous animals from the image, the animal hazard degree judgment section may judge one of the detected candidates for the hazardous animals that is present in a position closest to the direction of travel of the vehicle, as a hazardous animal. 
     The image capturing device may include a single image capturing device. Though the single image capturing device is unable to accurately detect the distance up to an object instantaneously unlike stereo cameras which can accurately detect the distance up to an object based on the parallax about the object between two images captured respectively thereby, even when the single image capturing device is used, the vehicle periphery monitoring apparatus of the present invention can judge whether the animal is a hazardous animal or not based on the posture shape of the animal. Thus, it is possible to accurately and instantaneously judge whether the animal is a hazardous animal or not from one image at low cost. 
     According to the present invention, it is judged whether or not the animal is a hazardous animal which may possibly affect the travel of the vehicle, not based simply on the position of the animal, but based on the posture shape of the animal. Therefore, it is possible to accurately judge whether the detected animal is a hazardous animal which may possibly affect the travel of the vehicle. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  a block diagram showing a configuration of a vehicle periphery monitoring apparatus according to an embodiment of the present invention; 
         FIG. 2  is a perspective view of a vehicle that incorporates therein the vehicle periphery monitoring apparatus shown in  FIG. 1 ; 
         FIG. 3  is a flowchart of an operation sequence of an image processing unit of the vehicle periphery monitoring apparatus; 
         FIG. 4  is a diagram showing an image of an animal, which is used in an animal detecting process; 
         FIG. 5  is a diagram showing another image of the animal, which is used in the animal detecting process; 
         FIG. 6  is a diagram illustrating a grayscale image in which a hazardous animal is displayed in highlight; 
         FIG. 7  is a diagram illustrating another grayscale image in which a hazardous animal is displayed in highlight; 
         FIG. 8  is a diagram illustrating still another grayscale image in which a hazardous animal is displayed in highlight; 
         FIG. 9  is a diagram illustrating yet another grayscale image in which a hazardous animal is displayed in highlight; 
         FIG. 10  is a diagram illustrating yet still another grayscale image in which a hazardous animal is displayed in highlight; 
         FIG. 11  is a diagram illustrating a grayscale image in which two hazardous animals are displayed in highlight; 
         FIG. 12  is a perspective view of a vehicle incorporating a vehicle periphery monitoring apparatus according to a modification; and 
         FIG. 13  is a schematic view of an inside of the vehicle as viewed by a driver, which includes a general-purpose display device displaying a hazardous animal in highlight in a grayscale image and an MID (Multi Information Display) device displaying an animal icon for making the driver conjure up the animal that is present in front of the vehicle. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     A preferred embodiment of the present invention will be described below with reference to the drawings. 
       FIG. 1  shows in block form the configuration of a vehicle periphery monitoring apparatus  10  according to an embodiment of the present invention.  FIG. 2  shows in perspective a vehicle  12  that incorporates therein the vehicle periphery monitoring apparatus  10  shown in  FIG. 1 . 
     As shown in  FIGS. 1 and 2 , the vehicle periphery monitoring apparatus  10  has an image processing unit  14  for controlling the vehicle periphery monitoring apparatus  10 , a single (monocular) infrared camera  16  (image capturing device) connected to the image processing unit  14 , a vehicle speed sensor  18  for detecting a vehicle speed Vs of the vehicle  12 , a brake sensor  20  for detecting a manipulated variable Br of a brake pedal (brake manipulated variable) that is operated by the driver of the vehicle  12 , a yaw rate sensor  22  for detecting a yaw rate Yr of the vehicle  12 , a speaker  24  for issuing an audible warning in the form of speech or the like, and an image display device  26  which comprises a HUD (Head Up Display)  26   a  for displaying images captured by the infrared camera  16  in order to enable the driver of the vehicle  12  to recognize a hazardous animal which may possibly affect the travel of the vehicle  12 . 
     The image display device  26  is not limited to the HUD (Head Up Display)  26   a , but may comprise a display device for displaying a map of a navigation system that is mounted in the vehicle  12 , or a display device (MID device: Multi-Information Display device) provided in a meter unit or the like for displaying mileage, etc. 
     According to the present invention, target objects whose risk of colliding with the vehicle  12  is to be judged, i.e., degree of hazard is to be judged, are animals. Therefore, the known process of judging the degree of risk concerning human being such as pedestrians (see JP2003-284057A and JP4267657B) will not be described below for an easier understanding of the present invention and also for the sake of brevity. 
     The image processing unit  14  detects an animal in front of the vehicle  12  based on an infrared image of the periphery of the vehicle  12  and signals, which represent a traveling state of the vehicle  12  (the vehicle speed Vs, the brake manipulated variable Br, and the yaw rate Yr in the present invention). If the image processing unit  14  judges that the detected animal is a hazardous animal which may possibly affect the travel of the vehicle  12 , the image processing unit  14  issues a warning, e.g., a beeping sound, from the speaker  24 , and displays the hazardous animal in a captured image, which is displayed as a grayscale image on the HUD  26   a , in such a highlighted manner that the hazardous animal is surrounded by a distinct color frame, which may be red or the like, thereby calling the attention of the driver. 
     The image processing unit  14  includes an input circuit such as a A/D converter circuit, etc., for converting an input analog signal into a digital signal, an image memory (storage unit  14   m ) for storing a digital image signal, a CPU (Central Processing Unit)  14   c  for performing various processing operations, a storage unit  14   m  including a RAM (Random Access Memory), which is used to store data during the processing by the CPU  14   c , and a ROM (Read Only Memory), which is used to store a program executed by the CPU  14   c , together with tables, maps, and templates {animal shaped templates: rightward, leftward, forward (and backward), etc. for deer, dogs, etc.}, a clock and timer, and an output circuit for supplying a drive signal for the speaker  24  and a display signal for the image display device  26 . The infrared camera  16 , the yaw rate sensor  22 , the vehicle speed sensor  18 , and the brake sensor  20  supply output signals, respectively, to the image processing unit  14  wherein the output signals are converted by the input circuit into digital signals, which are supplied to the CPU  14   c.    
     The CPU  14   c  of the image processing unit  14  reads the supplied digital signals, executes the program while referring to the tables, the maps, and the templates, thereby functioning as various functioning means (also referred to as functioning sections), and supplies drive signals, i.e., a speech signal and a display signal, to the speaker  24  and the image display device  26 . Such functions may also be implemented by way of hardware. 
     According to the present embodiment, the image processing unit  14  has an animal detection processor  104  and an animal hazard degree judgment section  105 . The animal hazard degree judgment section  105  includes a posture shape detector  106  and an attention calling processor  108 . 
     Basically, the image processing unit  14  runs an object recognition processing (object detection processing) program for recognizing an object by comparing an image acquired by the infrared camera  16  with pattern templates representing animal shapes, human body shapes, vehicle shapes, and artificial structure shapes which are stored in the storage unit  14   m.    
     As shown in  FIG. 2 , the infrared camera  16  is mounted on the front bumper of the vehicle  12  at a central position in the transverse directions of the vehicle  12 . The infrared camera  16  has such characteristics that, as the temperature of an object the image of which is captured by the infrared camera  16  is higher, the output signal (captured image signal) of the infrared camera  16  exhibits a higher level, i.e., a higher brightness level. 
     The HUD  26   a  is arranged so as to display a screen on the front windshield of the vehicle  12  at a position that does not obstruct the field of vision of the driver seated on the driver&#39;s seat in the vehicle  12 . 
     The image processing unit  14  performs the above functions so as to convert an analog video signal, which is generated by the infrared camera  16 , into digital data at a frame clock interval or period of several tens ms, e.g., 1 second per 30 frames [ms], to store the digital data in the storage unit  14   m  (image memory), and to carry out various processing operations on images in front of the vehicle  12 , which are stored in the storage unit  14   m.    
     The animal detection processor  104  extracts an image segment of an animal candidate from the image in front of the vehicle  12  that is stored in the storage unit  14   m , and detects the extracted image segment as an animal candidate. 
     The posture shape detector  106  of the animal hazard degree judgment section  105  detects the posture shape of the animal candidate that has been detected by the animal detection processor  104 . The posture shape may represent whether the animal candidate shows all legs, whether the neck of the animal candidate is directed upwardly or downwardly with respect to the torso thereof, whether the face direction of the animal candidate faces to the right or the left, and whether a portion of the animal candidate that contacts the road surface is its legs or its torso. 
     The animal hazard degree judgment section  105  judges whether the animal candidate is a hazardous animal which may possibly affect the travel of the vehicle  12  or not based on the posture shape of the animal candidate detected by the posture shape detector  106 . If the animal hazard degree judgment section  105  judges that the animal candidate is a hazardous animal, then the attention calling processor  108  of the animal hazard degree judgment section  105  performs an attention calling process for indicating to the driver, i.e., warning the driver, that the animal candidate is a hazardous animal. 
     A process of calculating a time until and a distance to the vehicle  12  collides with an object by use of the single infrared camera  16  will be described below. The image processing unit  14  calculates a rate of change Rate of the size of an image segment of one monitored object (animal in this case) between images that are captured at the frame clock interval or period (predetermined time interval) by the infrared camera  16 , calculates a time (also referred to as “collision margin time”) TTC (Time To Contact or Time To Collision), which represents a time it takes the monitored object (animal) to arrive at the vehicle  12 , using the rate of change Rate, and calculates the position of the monitored object (animal) in an actual space, i.e., a distance Z from the vehicle  12  to the monitored object (animal). 
     The collision margin time TTC it takes for the monitored object (animal) to arrive at the vehicle  12  can be determined from the rate of change Rate (determined from the images) and an image capturing interval (frame clock period) dT (known), which is a predetermined time interval, in a manner as disclosed in JP4267657B, according to the following expression (1):
 
 TTC=dT ×Rate/(1−Rate)  (1)
 
     The rate of change Rate can be determined from the ratio of the width or length WO (which may be stored as the number of pixels) of the monitored object (animal) in the previously captured image thereof to the width or length W 1  (the number of pixels) of the monitored object (animal) in the presently captured image thereof (Rate=WO/W 1 ). 
     The distance Z up to the monitored object (animal) can be determined, as disclosed in JP4267657B, according to the following expression (2):
 
 Z =Rate× Vs×dT /(1−Rate)  (2)
 
where Vs represents, more accurately, the relative speed between the monitored object (animal) and the vehicle  12 . The relative speed is equal to the vehicle speed Vs if the monitored object (animal) stays still.
 
     Basically, the vehicle periphery monitoring apparatus  10  is constructed and operates as described above. Detailed operation of the vehicle periphery monitoring apparatus  10  will be described below with reference to a flowchart shown in  FIG. 3 . 
     First, in step S 1 , the image processing unit  14  judges the travelling state of the vehicle  12 , i.e., whether the vehicle  12  is traveling or is at rest, from the vehicle speed Vs detected by the vehicle speed sensor  18 . If the vehicle  12  is at rest (step S 1 : NO), then the operation sequence shown in  FIG. 3  is stopped. 
     If the vehicle  12  is traveling (step S 1 : YES), then in step S 2  the image processing unit  14  acquires a captured infrared image, which is represented by an analog image signal generated by the infrared camera  16  in each frame within a predetermined angular field in front of the vehicle  12 . The image processing unit  14  converts the analog image signal into a digital image signal, which represents a grayscale image, stores the grayscale image in the image memory (storage unit  14   m ), carries out a binarizing process for converting the grayscale image into a binary image, in which areas brighter than a predetermined brightness threshold value are represented by a pixel value of “1” (white) and areas darker than the predetermined brightness threshold value are represented by a pixel value of “0” (black), and then stores the binary image in each frame in the storage unit  14   m  such that the binary images are associated with the respective frames. In the binarizing process, a cluster (human object candidate) of a head, shoulders, a torso, and two legs is detected as a cluster of pixel values of “1” (set). Further, regarding an animal (quadruped animal in the present embodiment) such as a dog (small animal), a deer (large animal), etc., a cluster (animal object candidate) of a head, a torso, a tail, and four legs is similarly detected as a cluster of pixel values of “1” (set). 
     In step S 3 , the image processing unit  14  carries out a labeling process that converts the pixels having values of “1” (white) of the binary image in each frame (image) into run-length data for each scanning line along the x direction (horizontal direction), while regarding lines having overlapping portions along the y direction (vertical direction) as an object. In addition, the image processing unit  14  applies labels to rectangles circumscribing such objects. For example, the circumscribing rectangles are labeled as animal candidate areas  152   a ,  152   b  shown in  FIGS. 4 and 5 . 
     In step S 4 , the animal detection processor  104  scans, downwardly and from the left to the right, the pixel values in a mask area  153   a , shown as a dot-and-dash-line area in  FIG. 4 , and a mask area  153   b , shown as a dot-and-dash-line area in  FIG. 5 , in the image which includes the labeled animal candidate areas  152   a ,  152   b , the mask areas  153   a ,  153   b  being slightly larger than the labeled animal candidate areas  152   a ,  152   b , respectively. If the animal detection processor  104  detects a succession of pixel values “0” representing a darker area, then the animal detection processor  104  determines the detected succession of pixels to be a boundary between each of animal candidates  162   a ,  162   b  (which is made up of a head  155 , a neck  157 , a torso  160 , and legs  159 , and is hereinafter referred to as an animal candidate  162 ), and a road surface  51  in the image, and regards the boundary as a lower end (also referred to as a road surface contact position) OBba, OBbb of the object. 
     Further, the animal detection processor  104  scans, upwardly from each of the lower ends OBba, OBbb of the animal candidates  162   a ,  162   b , from the left to the right, the pixel values in each of the mask areas  153   a ,  153   b . If the animal detection processor  104  detects a scanned zone where the brightness changes vertically (e.g., a zone where pairs of pixel values “1” and “0” are roughly successive in the binary image), then the animal detection processor  104  determines the detected zone to be a boundary between each of the animal candidates  162   a ,  162   b  and the background, and regards the boundary as an upper end OBta, OBtb of the object. 
     There are various ways of judging whether an object candidate is an animal candidate  162  ( 162   a  in  FIG. 4  or  162   b  in  FIG. 5 ). For example, if an object candidate has a horizontally long region (corresponding to the torso  160 ) wherein the ratio W 2 /H 2  of a horizontal width W 2  to a vertical width H 2  is in a range greater than a value “1” {(W 2 /H 2 )&gt;1} and two or more regions (up to four regions corresponding to the legs  159 ) existing beneath the horizontally long region wherein the ratio W 3 /H 3  of a width W 3  between the left and right ends of the two or more regions to a vertical width H 3  is greater than a value “1” {(W 3 /H 3 )&gt;1}, then the animal detection processor  104  judges the object candidate as an animal candidate  162 . 
     Furthermore, for example, if the animal detection processor  104  detects three or more legs  159 , preferably four legs  159 , beneath the torso  160 , then the animal detection processor  104  may judge the object candidate as an animal candidate  162 . 
     In addition, if a horizontal edge line on the upper end of the torso  160 , i.e., a horizontal line contacting the upper end at a height H 1  in  FIGS. 4 and 5 , intersects with the head  155  ( FIG. 4 ) or if the head  155  is positioned below the horizontal edge line on the upper end of the torso  160  ( FIG. 5 ), then the animal detection processor  104  may judge the object candidate as an animal candidate  162 . 
     In step S 5 , the animal detection processor  104  judges the result of the animal detecting process in step S 4 . If the animal detection processor  104  detects at least one animal candidate  162  in step S 5  (step S 5 : YES), then an animal hazard degree judging process is carried out in step S 6  to judge whether the animal candidate  162  is a hazardous animal which may possibly affect the travel of the vehicle  12 , i.e., which may possibly collide with the vehicle  12 , or not. If the animal detection processor  104  does not detect an animal candidate  162  (step S 5 : NO), the operation sequence from step S 1  is repeated. 
     In step S 7 , based on the result of the animal hazard degree judging process in step S 6 , if a hazardous animal is detected (step S 7 : YES), then an attention calling process is carried out to call attention of the driver to the detected hazardous animal in step S 8 . In step S 7 , if a hazardous animal is not detected (step S 7 : NO), then the operation sequence from step S 1  is repeated. 
     The animal hazard degree judging process carried out by the animal hazard degree judgment section  105  in step S 6  and the attention calling process carried out by the attention calling processor  108  in step S 8  will be described in detail below. 
     The animal hazard degree judgment section  105  operates the posture shape detector  106  to detect a posture shape of an animal candidate  162 , and judges whether the animal candidate  162  is a hazardous animal which may possibly affect the travel of the vehicle  12  or not based on the detected posture shape. If a plurality of animal candidates  162  are detected in the captured image, then the animal hazard degree judgment section  105  judges one of the detected animal candidates  162  that has the highest risk of affecting the travel of the vehicle  12  as a hazardous animal. 
     Specifically, according to a first judging process carried out by the animal hazard degree judgment section  105  using the posture shape detector  106 , if the posture shape detector  106  detects legs  159  in the posture shape of an animal candidate  162 , then the animal hazard degree judgment section  105  judges the animal candidate  162  with the detected legs  159  as a hazardous animal. 
     Then, the attention calling processor  108  displays the animal candidate  162  judged as a hazardous animal in highlight in the image (screen). 
       FIG. 6  shows a grayscale image (video image)  200  displayed on the HUD  26   a.    
     The grayscale image  200  shown in  FIG. 6  has a horizontally central position representing the frontal direction of the infrared camera  16  on the vehicle  12 . The grayscale image  200  includes a road  202  beneath the center thereof. The road  202  has a right road side edge (right road edge)  204  and a left road side edge (left road edge)  206 , which are extracted by an edge detecting process or the like. 
     The grayscale image  200  also includes a tuft  208  of grass in an area on the left side of the center thereof in  FIG. 6 . Animals often tend to be present on the tuft  208  of grass outside of the road  202 . It is possible to judge whether an animal is present on the road  202  or outside of the road  202  by judging whether there are legs  159  ( FIGS. 4 and 5 ) or not. 
     The grayscale image  200  shown in  FIG. 6  includes two displayed animals  210 ,  212  (deer in this case) which correspond to the respective animal candidates  162  ( FIG. 4  or  5 ) that are detected by the animal detection processor  104 . The left animal  210  has no legs detected, and the central animal  212  has legs  159  ( FIGS. 4 and 5 ) detected. 
     According to the first judging process, the animal hazard degree judgment section  105  judges the animal candidate  162  with the detected legs  159  as a hazardous animal. Therefore, the central animal  212  is displayed in such a highlighted manner that the central animal  212  is surrounded by a red thick frame  214 , for warning the driver. The left animal  210  is displayed and surrounded by a yellow thin frame  216  for warning the driver. When the central animal  212  is displayed and highlighted by surrounding the central animal  212  by the red thick frame  214 , the speaker  24  issues a warning at the same time. 
     According to a second judging process, when the posture shape detector  106  detects that the angle θ of the neck  157  with respect to the torso  160  is directed upwardly (θ&gt;0) in the posture shape of an animal candidate  162 , the animal hazard degree judgment section  105  judges the animal candidate  162  with the upward neck  157 , i.e., the animal candidate  162   a  shown in  FIG. 4 , as a hazardous animal. 
       FIG. 7  shows a grayscale image (video image)  220  displayed on the display area of the HUD  26   a.    
     The grayscale image  220  shown in  FIG. 7  includes two displayed animals  222 ,  224  (deer in this case) which correspond to the respective animal candidates  162  that are detected by the animal detection processor  104 . The left animal  222  has a neck  157  directed downwardly (see  FIG. 5 ), and the right animal  224  has a neck  157  directed upwardly (see  FIG. 4 ). Since the animal  222  with the neck  157  directed downwardly does not jump out abruptly, the animal  224  with the neck  157  directed upwardly is more hazardous. 
     According to the second judging process, the animal hazard degree judgment section  105  judges the animal candidate  162   b  with the upward neck  157  as a hazardous animal. Therefore, the right animal  224  is displayed in such a highlighted manner that the right animal  224  is surrounded by a red thick frame  214 , for warning the driver. The left animal  222  is displayed and surrounded by a yellow thin frame  216 , for warning the driver. When the right animal  224  is displayed in such a highlighted manner with the right animal  224  being surrounded by the red thick frame  214 , the speaker  24  issues a warning at the same time. 
     According to a third judging process, when the posture shape detector  106  detects, in the posture shape of an animal candidate  162 , that the distance from the position of the animal candidate  162  to a road side edge to which the face of the animal candidate  162  is directed is greater than a predetermined distance, e.g., that the animal candidate  162  is positioned outside of the horizontally central position of the image, i.e., substantially the transversely central position of the road  202 , the animal hazard degree judgment section  105  judges the animal candidate  162  as a hazardous animal. 
     Specifically, a grayscale image  230  shown in  FIG. 8  includes two displayed animals  232 ,  234  (deer in this case) which correspond to the respective animal candidates  162  that are detected by the animal detection processor  104 , wherein the faces of the animals  232 ,  234  are directed toward the right road side edge  204 . The distance “a” from the left animal  232  to the right road side edge  204  is greater than a predetermined distance, whereas the distance “b” from the right animal  234  to the right road side edge  204  is smaller than the predetermined distance (a&gt;b). 
     The animal  232  which is spaced by the longer distance “a” from the road side edge to which the face of the animal  232  is directed (wherein the direction is regarded as the direction of the animal&#39;s movement) is regarded as staying on the road  202  for a longer period of time than the animal  234  which is spaced by the shorter distance “b” from the road side edge. Therefore, the animal hazard degree judgment section  105  judges the animal  232  as a hazardous animal. 
     According to the third judging process, the animal hazard degree judgment section  105  judges the left animal  232  as a hazardous animal. Therefore, the left animal  232  is displayed in a highlighted manner such that the left animal  232  is surrounded by a red thick frame  214 , for warning the driver. The right animal  234  is displayed and surrounded by a yellow thin frame  216 , for warning the driver. When the left animal  232  is displayed in a highlighted manner with the surrounding red thick frame  214 , the speaker  24  issues a warning at the same time. 
     According to a fourth judging process, if the animal hazard degree judgment section  105  detects a plurality of animal candidates having similar hazard degrees from the image according to either one of the first through third judging processes, e.g., in a case where the third judging process is performed on animals  242 ,  244  in a grayscale image  240  shown in  FIG. 9 , if it is detected that the distance “a” from the left animal  242 , which faces toward the right of the road  202 , up to the right road side edge  204  in  FIG. 9  is substantially the same as the distance “b” from the right animal  244 , which faces toward the left of the road  202 , up to the left road side edge  206  in  FIG. 9  (i.e., a≈b), the animal hazard degree judgment section  105  compares road surface contact positions OBb 1 , OBb 2  where the lower ends of the respective animals  242 ,  244  contact the road  202 , and judges the animal  244  whose road surface contact position OBb 2  is closer to the vehicle  12  as a hazardous animal. 
     According to the fourth judging process, the animal hazard degree judgment section  105  judges the right animal  244  closer to the vehicle  12  as a hazardous animal. Therefore, the right animal  244  is displayed in a highlighted manner such that the right animal  244  is surrounded by a red thick frame  214 , for warning the driver. The left animal  242  is displayed and surrounded by a yellow thin frame  216 , for warning the driver. When the right animal  244  is displayed in highlight with the surrounding red thick frame  214 , the speaker  24  issues a warning at the same time. 
     According to a fifth judging process, when the animal hazard degree judgment section  105  detects a plurality of animal candidates having similar hazard degrees from the image according to either one of the first through third judging processes, e.g., in a case where the first judging process is performed on animals  252 ,  254  in a grayscale  250  shown in  FIG. 10 , if it is detected that both the animals  252 ,  254  show their legs, the animal hazard degree judgment section  105  judges the animal  252  that is closer to an image center  256  (i.e., closer to the direction of travel of the vehicle  12 ) as a more hazardous animal than the animal  254  that is more spaced away from the image center  256 . 
     According to the fifth judging process, the animal hazard degree judgment section  105  judges the left animal  252  that is positioned closer to the direction of travel of the vehicle  12  as a hazardous animal. Therefore, the left animal  252  is displayed in a highlighted manner such that the left animal  252  is surrounded by a red thick frame  214 , for warning the driver. The right animal  254  is displayed and surrounded by a yellow thin frame  216 , for warning the driver. When the left animal  252  is displayed in highlight with the surrounding red thick frame  214 , the speaker  24  issues a warning at the same time. 
     If it is not possible to judge which one of plural animals has a higher hazard degree according to the first through fifth judging processes, e.g., if animals  262 ,  264  are present at respective positions in a grayscale image  260  shown in  FIG. 11 , then, according to a sixth judging process, the animal hazard degree judgment section  105  judges both the animals  262 ,  264  as hazardous animals, displays them in a highlighted manner such that each of the animals  262 ,  264  is surrounded by a red thick frame  214 , for warning the driver, and also issues a warning through the speaker  24 . 
     [Overview of the Embodiment] 
     As described above, the vehicle periphery monitoring apparatus  10  according to the above embodiment detects a hazardous animal from an image captured by the single infrared camera  16  mounted on the vehicle  12  and warns the driver of the vehicle  12  about the detected hazardous animal. 
     The vehicle periphery monitoring apparatus  10  has the animal detection processor  104  for detecting an animal as an object to be monitored from the image and the animal hazard degree judgment section  105  for judging whether the animal is a hazardous animal which may possibly affect the travel of the vehicle  12  or not depending on the posture shape of the animal detected from the image. 
     According to the present embodiment, it is judged whether or not the animal is a hazardous animal which may possibly affect the travel of the vehicle  12 , not based simply on the position of the animal, but based on the posture shape of the animal. Therefore, it is possible to accurately judge a hazardous animal, and hence to appropriately call attention of the driver to the hazardous animal. Since the hazard degree of the animal is judged depending on the posture shape of the animal, it is possible to judge a hazardous animal without using distance information and motion vectors. Thus, its processing load is reduced, and then it becomes possible to judge a hazardous animal in a reduced judging time. Therefore, the vehicle periphery monitoring apparatus  10  can use a low-rate CPU and can be reduced in cost. 
     For example, according to the first judging process, if the animal hazard degree judgment section  105  detects legs  159  (see  FIGS. 4 and 5 ) in the posture shape of the animal, then the animal hazard degree judgment section  105  may judge the animal as a hazardous animal. As shown in  FIG. 6 , the animal  212  positioned on the road  202  has its legs  159  detected, and the animal  210  positioned outside of the road  202  does not have its legs  159  detected because the animal is often positioned on the tuft  208  of grass. The animal hazard degree judgment section  105  can judge whether an animal is positioned on the road  202  or outside of the road  202  by judging whether the animal shows its legs or not. 
     According to the second judging process, if the animal hazard degree judgment section  105  detects that the angle θ of the neck  157  with respect to the torso  160  is directed upwardly (see  FIG. 4 ) in the posture shapes of the animals  222 ,  224 , as shown in  FIG. 7 , then the animal hazard degree judgment section  105  may judge the animal with the upward neck  157  as a hazardous animal. Since the animal  222  with the angle θ of the neck  157  with respect to the torso  160  being directed downwardly, does not jump out abruptly, the animal hazard degree judgment section  105  can judge the animal  224  with the neck  157  directed upwardly as more hazardous than the animal  222  with the neck  157  directed downwardly (see  FIG. 7 ). 
     According to the third judging process, if the animal hazard degree judgment section  105  detects, in the posture shapes of the animals  232 ,  234 , that the distance “a” from the position of the animal  232  to the right road side edge  204  to which the face of the animal  232  is directed is greater than a predetermined distance, i.e., ½ of the width of the road  202 , as shown in  FIG. 8 , then the animal hazard degree judgment section  105  may judge the animal  232  as a hazardous animal. If the distance “a” from the position of the animal  232  to the right road side edge  204  toward which the face of the animal  232  is directed is greater than the predetermined distance, then the animal  232  can be regarded as staying on the road  202  for a long period of time, and thus the animal  232  can be judged as a hazardous animal. 
     According to the fourth judging process, if the animal hazard degree judgment section  105  detects a plurality of candidates for animals having high hazard degrees from the grayscale image  240 , as shown in  FIG. 9 , then the animal hazard degree judgment section  105  may judge one  244  of the candidates for the hazardous animals  242 ,  244  whose road surface contact position OBb 2  is closest to the vehicle  12 , as a hazardous animal. 
     According to the fifth judging process, if the animal hazard degree judgment section  105  detects a plurality of candidates for animals having high hazard degrees from the grayscale image  250 , as shown in  FIG. 10 , then the animal hazard degree judgment section  105  may judge one  252  of the candidates for the animals  252 ,  254  that is closer to the direction of travel of the vehicle  12 , i.e., the image center  256 , as a hazardous animal. 
     According to the above embodiment, though the single infrared camera  16  is unable to accurately detect the distance up to an object instantaneously unlike stereo cameras which can accurately detect the distance up to an object based on the parallax of the object between two images captured respectively thereby, the single infrared camera  16  is used. However, since it is judged whether the monitored animal is a hazardous animal or not, based on the posture shape of the animal, it is possible to accurately and instantaneously judge whether the monitored animal is a hazardous animal or not from one image. Therefore, the vehicle periphery monitoring apparatus  10  can be reduced in cost. 
     The present invention is not limited to the above embodiment, but may employ various arrangements based on the disclosure of the present description. 
     For example, as shown in  FIG. 12 , a vehicle periphery monitoring apparatus may have a set of left and right infrared cameras  16 R,  16 L mounted on a vehicle  12 A. The infrared cameras  16 R,  16 L for use as stereo cameras are mounted on a front bumper of the vehicle  12 A in respective positions that are substantially symmetrical with respect to the center of the vehicle  12 A in the transverse directions thereof. The two infrared cameras  16 R,  16 L have parallel optical axes, respectively, and are fixed in position at the same height from the road surface. As well known in the art, the vehicle periphery monitoring apparatus with the set of left and right infrared cameras  16 R,  16 L regards high-temperature areas in an image of the periphery of the vehicle  12 A which is captured by the infrared cameras  16 R,  16 L as objects, calculates the distance up to one object based on the parallax of the one object in the left and right images captured by the infrared cameras  16 R,  16 L according to triangulation, detects an object that may affect the travel of the vehicle  12 A, i.e., an animal having a possibility of collision with the vehicle  12 A, based on the positions of the objects, instantaneously judges whether the object is a hazardous animal or not, and generates an attention calling output signal if the object is judged as a hazardous object. 
     The vehicle periphery monitoring apparatus may employ a general digital video camera (image capturing device) for capturing an image of an ordinary visible range as a single camera or stereo camera as with the present embodiment, rather than the infrared camera or cameras. 
     As shown in  FIG. 13 , which illustrates in an upper section thereof an inside of the vehicle as viewed by the driver while the vehicle  12  is being driven at night, the image display device  26  includes a display device  26   b  (general-purpose display device) disposed centrally on a dashboard  290  for use with a navigation apparatus and an audio apparatus. The display device  26   b  displays a grayscale image (video image)  280  captured by the infrared camera  16  ( 16 L), as shown at an enlarged scale in a lower right section of  FIG. 13 , the grayscale image  280  including an image of a hazardous animal  282  that represents a hazardous animal  282   r  which is actually present in a far position in front of the front windshield of the vehicle and that is displayed and surrounded by a red thick frame  214 , for warning the driver. At the same time, the speaker  24  issues a warning about the hazardous animal  282   r.    
     When the display device  26   b  as the general-purpose display device displays the hazardous animal  282  surrounded by the red thick frame  214 , an MID (Multi-Information Display) device  26   c  disposed centrally in a meter unit  292  in front of the driver as a display unit of relatively low resolution may display an animal icon  296  (deer icon in this case) as shown at an enlarged scale in a lower left section of  FIG. 13 , thereby for warning the driver. According to the present embodiment, the animal icon  296  is not displayed unless the hazardous animal  282  surrounded by the red thick frame  214  is displayed on the display device  26   b . It is desirable that the animal icon  296  should be displayed in a striking color such as yellow or the like or in a blinking fashion in order to draw the driver&#39;s attention to the hazardous animal. The three lines that are displayed beneath the animal icon  296  represent road icons for making the driver conjure up the left and right edges and the center line of the road which are displayed at all times when the vehicle periphery monitoring apparatus  10  is activated.