Patent Publication Number: US-2013235202-A1

Title: Vehicle periphery monitoring apparatus and method of determining type of object for use in vehicle periphery monitoring apparatus

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is based upon and claims the benefit of priority from Japanese Patent Application No. 2012-053962 filed on Mar. 12, 2012, the contents of which are incorporated herein by reference. 
     BACKGROUND OF THE INVENTION 
     1. Field of the Invention 
     The present invention relates to a vehicle periphery monitoring apparatus for monitoring the periphery of a vehicle based on an image captured by an infrared camera mounted on the vehicle, and more particularly to a vehicle periphery monitoring apparatus and a method of determining the type of an object for use in such a vehicle periphery monitoring apparatus, which are suitable for use when the vehicle is driving at night or in dark places. 
     2. Description of the Related Art 
     As disclosed in Japanese Laid-Open Patent Publication No. 2003-284057 (hereinafter referred to as “JP2003-284057A”), there has heretofore been known a vehicle periphery monitoring apparatus incorporated in a driver&#39;s own vehicle which detects an object such as a pedestrian or the like that could possibly contact the driver&#39;s own vehicle from images (a grayscale image and its binarized image) of the periphery of the driver&#39;s own vehicle captured by infrared cameras, and provides the driver with information about the detected object. 
     The vehicle periphery monitoring apparatus disclosed in JP2003-284057A detects a high-temperature area of the two images captured by a pair of left and right infrared cameras (stereo camera system) as an object, and calculates the distance up to the object by determining the parallax of the object in the two images. The vehicle periphery monitoring apparatus then detects an object such as a pedestrian or the like that is likely to affect the traveling of the driver&#39;s own vehicle, i.e., that could possibly contact the driver&#39;s own vehicle, from the moving direction and position of the object detected in the captured images (see paragraphs [0014], [0018] of JP2003-284057A). 
     However, since such vehicle periphery monitoring apparatuses with a pair of left and right infrared cameras are expensive, they have been incorporated in limited luxury cars only. 
     In an attempt to reduce the cost of the vehicle periphery monitoring apparatus, a vehicle periphery monitoring apparatus disclosed in Japanese Patent No. 4521642 (hereinafter referred to as “JP4521642B2”) employs a single vehicle-mounted infrared camera which captures at least two images (two frames) of an object in the periphery of a vehicle at a given interval of time. As the relative speed between the object and the vehicle incorporating the vehicle periphery monitoring apparatus is higher, the size of an image of the object in the image captured later changes more greatly from the size of an image of the object in the image captured earlier. As the relative speed between the object and the vehicle is higher, the object that is present ahead of the vehicle reaches the vehicle in a shorter period of time. Consequently, even a single infrared camera is able to monitor the periphery of a vehicle by estimating a period of time which an object takes to reach the vehicle, so-called TTC (Time To Contact or Time to Collision), from a rate of change of the size of images of an object which are captured at a given interval of time (see paragraphs [0019], [0020] of JP4521642B2). 
     SUMMARY OF THE INVENTION 
     According to JP4521642B2, the vehicle periphery monitoring apparatus judges whether an object that is imaged at different times is a person or a vehicle by dividing the object into local areas depending on the object, i.e., a person or a vehicle, making images of the object that are captured at different times equal in size to each other, and decides that the object is a person or a vehicle if the degree of correlation between the local areas is equal to or greater than a threshold value. 
     When a vehicle which incorporates the vehicle periphery monitoring apparatus disclosed in JP2003-284057A or JP4521642B2 is driving at night, it is capable of displaying a video image of a pedestrian walking ahead of the vehicle which has been detected by an infrared camera as a target object to be monitored that cannot clearly be seen by the driver of the vehicle. 
     When the vehicle periphery monitoring apparatus of the related art detects a person, i.e., a pedestrian, at night or in dark places, it can easily identify the shape of the head of the person from the image captured by the infrared camera because the head is exposed and has a high surface temperature and the head has a round shape. 
     When the infrared camera of the vehicle periphery monitoring apparatus of the related art captures the front end of another vehicle, e.g., an oncoming vehicle, at night, it can easily identify the headlights thereof that are positioned at respective ends in the transverse directions of the other vehicle. When the infrared camera of the vehicle periphery monitoring apparatus captures the rear end of another vehicle, e.g., a preceding vehicle running ahead in the same direction, at night, it can easily identify the taillights thereof that are positioned at respective ends in the transverse directions of the other vehicle. 
     However, since the headlights and taillights of other vehicles are not significantly different from the heads of pedestrians in height from the road, and the shapes of the lights are similar to the shapes of the heads of pedestrians in infrared images (video images), the vehicle periphery monitoring apparatus of the related art finds it difficult to distinguish between the headlights or taillights of other vehicles and the heads of pedestrians. Furthermore, as described later, the vehicle periphery monitoring apparatus of the related art occasionally fails to decide that there are two headlights or taillights on other vehicles on account of heat emitted by the exhaust pipes, etc. of the other vehicles and spread to the vehicle bodies of the other vehicles. 
     It is an object of the present invention to provide a vehicle periphery monitoring apparatus and a method of determining the type of an object for use in such a vehicle periphery monitoring apparatus which are capable of accurately distinguishing between another vehicle and a pedestrian. 
     According to the present invention, there is provided a vehicle periphery monitoring apparatus for detecting an object in the periphery of a vehicle based on an image captured by an infrared camera mounted on the vehicle, and determining the type of the detected object, comprising a pedestrian head candidate extractor for extracting a pedestrian head candidate from the image, an other vehicle candidate detector for detecting a high-luminance area which is greater in area than the pedestrian head candidate and has a horizontal length equal to or greater than a prescribed width, within a prescribed range beneath or below the extracted pedestrian head candidate, and an other vehicle determiner for determining the pedestrian head candidate as part of another vehicle when the other vehicle candidate detector detects the high-luminance area. 
     According to the present invention, there is also provided a vehicle periphery monitoring apparatus for detecting an object in the periphery of a vehicle based on an image captured by an infrared camera mounted on the vehicle, and determining the type of the detected object, comprising pedestrian head candidate extracting means for extracting a pedestrian head candidate from the image, other vehicle candidate detecting means for detecting a high-luminance area which is greater in area than the pedestrian head candidate and has a horizontal length equal to or greater than a prescribed width, within a prescribed range beneath the extracted pedestrian head candidate, and other vehicle determining means for determining the pedestrian head candidate as part of another vehicle when the other vehicle candidate detecting means detects the high-luminance area. 
     According to the present invention, there is further provided a method of determining a type of an object for use in a vehicle periphery monitoring apparatus for detecting an object in the periphery of a vehicle based on an image captured by an infrared camera mounted on the vehicle, comprising a pedestrian head candidate extracting step of extracting a pedestrian head candidate from the image, an other vehicle candidate detecting step of detecting a high-luminance area which is greater in area than the pedestrian head candidate and has a horizontal length equal to or greater than a prescribed width, within a prescribed range beneath the extracted pedestrian head candidate, and an other vehicle determining step of determining the pedestrian head candidate as part of another vehicle when the high-luminance area is detected in the other vehicle candidate detecting step. 
     According to the present invention, when a high-luminance area which is greater in area than the pedestrian head candidate and has a horizontal length equal to or greater than a prescribed width is detected in a prescribed range beneath the pedestrian head candidate that is extracted from the image acquired by the infrared camera, the pedestrian head candidate is determined as part of another vehicle. Consequently, the other vehicle and a pedestrian can be distinguished from each other highly accurately. 
     When the other vehicle candidate detector detects the pedestrian head candidate in a rigid body (an object whose shape remains unchanged) in the image, the other vehicle determiner may determine the rigid body as the other vehicle. 
     The other vehicle candidate detector may further detect an engine exhaust pipe candidate or a tire candidate in the image, and when the other vehicle candidate detector detects the high-luminance area above the engine exhaust pipe candidate or the tire candidate, the other vehicle determiner may determine an object including the pedestrian head candidate and the engine exhaust pipe candidate or an object including the pedestrian head candidate and the tire candidate as the other vehicle. 
     When the other vehicle candidate detector further detects another high-luminance area equal to or greater than a prescribed area or a low-luminance area equal to or greater than a prescribed area above the pedestrian head candidate in the image, the other vehicle determiner may determine the pedestrian head candidate as part of the other vehicle regardless whether or not the other vehicle candidate detector detects the high-luminance area which is greater in area than the pedestrian head candidate and has the horizontal length. 
     In this case, if the temperature outside of the vehicle is equal to or higher than a first temperature, then the other vehicle determiner may judge whether or not there is a low-luminance area which is greater in area than the pedestrian head candidate, above the pedestrian head candidate, and if the temperature outside of the vehicle is equal to or lower than a second temperature which is lower than the first temperature, then the other vehicle determiner may judge whether or not there is a high-luminance area which is greater in area than the pedestrian head candidate, above the pedestrian head candidate. In this manner also, the other vehicle can be detected. 
     According to the present invention, as described above, when a high-luminance area which is horizontally greater in area than the pedestrian head candidate and has a horizontal length equal to or greater than a prescribed width is detected within a prescribed range beneath the pedestrian head candidate that is extracted from the image acquired by the infrared camera, the pedestrian head candidate is determined as part of another vehicle. Therefore, another vehicle and a pedestrian can be distinguished from each other highly accurately. 
     The above and other objects, features, and advantages of the present invention will become more apparent from the following description when taken in conjunction with the accompanying drawings in which preferred embodiments of the present invention are shown by way of illustrative example. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram of a vehicle periphery monitoring apparatus according to an embodiment of the present invention; 
         FIG. 2  is a perspective view of a vehicle which incorporates 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 a pedestrian candidate; 
         FIG. 5  is a diagram showing an image of a vehicle which could possibly be detected in error as a pedestrian candidate; 
         FIG. 6  is a diagram showing another image of a vehicle which could possibly be detected in error as a pedestrian candidate; 
         FIG. 7  is a diagram showing an image of a vehicle which could possibly be detected in error as a pedestrian candidate according to another embodiment of the present invention; 
         FIG. 8A  is a diagram showing a present image; 
         FIG. 8B  is a diagram showing a past image; 
         FIG. 9  is a table showing the coordinates of various parts of the present and past images; and 
         FIG. 10  is a perspective view of a vehicle which incorporates a vehicle periphery monitoring apparatus according to a modification. 
     
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     Preferred embodiments of the present invention will be described in detail below with reference to the drawings. 
       FIG. 1  shows in block form a vehicle periphery monitoring apparatus  10  according to an embodiment of the present invention, and  FIG. 2  shows in perspective a vehicle (hereinafter also referred to as “driver&#39;s own vehicle”)  12  which incorporates the vehicle periphery monitoring apparatus  10  shown in  FIG. 1 . 
     As shown in  FIGS. 1 and 2 , the vehicle periphery monitoring apparatus  10  includes 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 depressed amount (brake depressed amount) Br of a brake pedal which 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 outputting a warning sound or the like, and an image display unit  26  comprising a HUD (Head Up Display)  26   a  for displaying an image captured by the infrared camera  16  to make the driver of the vehicle  12  recognize an object (moving object, target object to be monitored) such as a pedestrian or the like that is likely to contact the vehicle  12 . 
     The image display unit  26  is not limited to the HUD  26   a , but may be a display unit for displaying a map, etc. of a navigation system incorporated in the vehicle  12  or a display unit (multi-information display unit) disposed in a meter unit for displaying fuel consumption information, etc. 
     The image processing unit  14  detects a target object to be monitored, such as a pedestrian or the like, in front of the vehicle  12 , from an infrared image of the periphery of the vehicle  12  and signals indicative of a traveling state of the vehicle  12 , i.e., signals representing the vehicle speed Vs, the brake depressed amount Br, and the yaw rate Yr. If the image processing unit  14  decides that it is highly likely for the vehicle  12  to collide with the target object to be monitored, then the image processing unit  14  outputs a warning sound, e.g., a succession of blips from the speaker  24 , and highlights the target object to be monitored in a captured image displayed as a grayscale image on the HUD  26   a , by surrounding the target object with a bright color frame such as a yellow or red frame, thereby arousing attention of the driver. 
     The image processing unit  14  includes an input circuit comprising an A/D converting circuit for converting analog signals input thereto into digital signals, an image memory (storage unit  14   m ) for storing digital image signals, a CPU (Central Processing Unit)  14   c  for performing various processing operations, a storage unit  14   m  including a RAM (Random Access Memory) for storing data being processed by the CPU  14   c  and a ROM (Read Only Memory) for storing a program executed by the CPU  14   c , tables, maps, and templates {pedestrian (human body) shape templates, vehicle shape templates, etc.}, a clock (clock section) and a timer (time measuring section), and an output circuit for outputting a drive signal for the speaker  24  and a display signal for the image display unit  26 . Output signals from the infrared camera  16 , the yaw rate sensor  22 , the vehicle speed sensor  18 , and the brake sensor  20  are converted by the A/D converting circuit into digital signals, which are then input to the CPU  14   c.    
     The CPU  14   c  of the image processing unit  14  reads the supplied digital signals and 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”), described below, to send the drive signal (e.g., sound signal, display signal) to the speaker  24  and the display signal to the image display unit  26 . The functioning means may alternatively be performed by pieces of hardware. 
     According to the present embodiment, the functioning sections of the image processing unit  14  include a pedestrian head candidate extractor  101 , an other vehicle candidate detector  102 , an other vehicle determiner  103  functioning as a target object determiner, a contact possibility determiner  106 , and an attention seeking output generation determiner  108 . When the pedestrian head candidate extractor  101  extracts a pedestrian head candidate from an image (captured image) acquired by the infrared camera  16 , the pedestrian head candidate extractor  101  also extracts a pedestrian candidate including a head candidate. In other words, the pedestrian head candidate extractor  101  also functions as a pedestrian candidate extractor. 
     The image processing unit  14  basically executes an object recognizing (distinguishing) program (object detecting program) for recognizing (distinguishing) an object by comparing an image captured by the infrared camera  16  with pattern templates representing human body shapes, animal shapes, vehicle shapes, and artificial structure shapes such as columns or the like including utility poles, which are stored in the storage unit  14   m.    
     As shown in  FIG. 2 , the infrared camera  16  is mounted in a front bumper of the vehicle  12  with an optical axis thereof extending parallel to the longitudinal axis of the vehicle  12 . The infrared camera  16  has such characteristics that its output signal (imaging signal) has a higher level (a higher luminance level) as the temperature of a target object imaged thereby is higher. 
     The HUD  26   a  is positioned to display its display screen on the front windshield of the vehicle  12  at such a position where it does not obstruct the field of front vision of the driver. 
     The image processing unit  14  converts a video signal output from the infrared camera  16  into digital data at frame clock intervals/periods of several tens milliseconds, e.g., 1 second/30 frames [ms], and stores the digital data in the storage unit  14   m  (image memory). The image processing unit  14  includes the above functioning means to perform various processing operations on an image of an area in front of the vehicle  12  which is represented by the digital data stored in the storage unit  14   m.    
     The pedestrian head candidate extractor  101  extracts an image portion of a target object to be monitored, such as a pedestrian, a vehicle (another vehicle), etc., from the image of the area in front of the vehicle  12  which is stored in the storage unit  14   m , and extracts a pedestrian head candidate having a prescribed size based on the extracted image portion. 
     The other vehicle candidate detector  102  detects a high-luminance area, to be described later, having an area greater than the area of the pedestrian head candidate detected by the pedestrian head candidate extractor  101  and a horizontal length equal to or greater than a prescribed width, within a prescribed range below the pedestrian head candidate. 
     When the other vehicle candidate detector  102  detects the high-luminance area, the other vehicle determiner  103  determines the pedestrian head candidate as part of the other vehicle. 
     The attention seeking output generation determiner  108  calculates a rate of change Rate of the size of the image portion of the target object to be monitored between images that are captured at the above frame clock intervals/periods (prescribed time intervals), estimates a period of time T which the target object to be monitored takes to reach the vehicle  12  using the rate of change Rate, calculates the position of the target object to be monitored in the actual space, and calculates a motion vector in the actual space of the target object to be monitored. 
     The period of time TTC (Time To Contact) that the target object to be monitored takes to reach the vehicle  12 , i.e., the period of time TTC that the target object to be monitored takes to contact the vehicle  12 , can be determined from the rate of change Rate (determined from the image) and image capturing intervals (frame clock periods) dT (known), which is a prescribed time intervals, according to the following expression (1): 
       TTC= dT  Rate/(1−Rate)  (1)
 
     The rate of change Rate is determined as a ratio between the width or length W0 (which may be stored as a number of pixels) of the target object to be monitored in an image captured earlier and the width or length W1 (which may be stored as a number of pixels) of the target object to be monitored in an image captured later (Rate=W0/W1). 
     The distance Z up to the target object to be monitored is determined from the following expression (2), which is provided by multiplying both sides of the expression (1) by the vehicle speed Vs: 
         Z =Rate  Vs dT /(1−Rate)  (2)
 
     Incidentally, more precisely the vehicle speed Vs should be replaced with a relative speed between the target object to be monitored and the vehicle  12 . In a case where the target object is not moving, the relative speed is equal to the vehicle speed Vs. 
     The attention seeking output generation determiner  108  calculates a positional change x (horizontal) and a positional change y (vertical) of the image portion of the target object to be monitored between the images that are captured at the prescribed time intervals, and determines a contact possibility that the target object to be monitored and the vehicle  12  will contact each other, based on the determined period of time TTC and the calculated positional changes (motion vector) x, y. 
     The vehicle periphery monitoring apparatus  10  is basically constructed as described above. An operation sequence of the vehicle periphery monitoring apparatus  10  will be described in detail below with reference to a flowchart shown in  FIG. 3 . 
     In step S 1  shown in  FIG. 3 , the image processing unit  14  judges whether the vehicle  12  is traveling or at rest based on, for example, the vehicle speed Vs detected by the vehicle speed sensor  18 . If the vehicle  12  is at rest (S 1 : NO), then the operation sequence is stopped. 
     If the vehicle  12  is traveling (S 1 : YES), then in step S 2  the image processing unit  14  acquires an infrared image of an area within a given angle of view in front of the vehicle  12 , which is represented by an output signal from the infrared camera  16  in each frame, converts the infrared image into a digital grayscale image, stores the digital grayscale image in the image memory (storage unit  14   m ), and binarizes the stored grayscale image. 
     More specifically, the image processing unit  14  performs a binarizing process on the grayscale image by converting areas brighter than a luminance threshold value for determining a human luminance level into “1” (white) and areas darker than the luminance threshold value into “0” (black) to generate a binarized image in each frame, and stores the binarized image in the storage unit  14   m.    
     In step S 3 , the image processing unit  14  detects (extracts), as shown in  FIG. 4 , a pedestrian candidate PCX comprising a head candidate  50 , a body candidate  52  including arms, and two leg candidates  54  of a pedestrian Pa. A substantially horizontal line interconnecting the lower ends of the two leg candidates  54  is regarded as a point of contact with a road surface  56 . 
     Since the head of a person has a high surface temperature and a round shape, the head candidate  50  can easily be extracted from the binarized image which corresponds to the grayscale image converted from the infrared image captured by the infrared camera  16 . The binarized image in each frame is stored in the storage unit  14   m.    
     Since the pedestrian candidate PCX is walking with its arms swinging and its legs moving up and down, its shape is changing as confirmed from the image in each frame. The pedestrian candidate PCX is thus not detected as a rigid body, such as another vehicle, whose shape remains unchanged between images in respective frames. 
     In step S 3 , when the height of an object having a head candidate  50  from the road surface  56  is within a prescribed height range, the object is estimated as a pedestrian candidate PCX, and its image is stored as being labeled as run-length data, i.e., a labeling process is performed on its image. At this time, the image thus processed is a large quadrangle-shaped image including a quadrangle circumscribing the pedestrian candidate PCX. If necessary, large quadrangle-shaped images including quadrangles circumscribing pedestrian candidates PCX are converted into images of one size in respective frames for easier image processing. 
     In the binarizing process in step S 2 , the image of another vehicle Car shown in  FIG. 5  is processed as follows: Lights  70   a ,  70   b  on laterally spaced left and right end portions of the other vehicle Car, such as headlights (oncoming car) or taillights (preceding car), a front grill (oncoming car) or an exhaust pipe  72  (preceding car) on a lower central portion of the other vehicle Car, and left and right tires  74   a ,  74   b  of the other vehicle Car are indicated as hatched regions because of their higher luminance level. 
     Other portions of the vehicle body of the other vehicle are indicated depending on the ambient temperature. If the ambient temperature is lower than another portion of the vehicle body of the other vehicle Car, the other portion is indicated as blank, with the background being sectioned by the shape of the other vehicle Car. 
     Incidentally, the road surface  56  can be detected based on a horizontal line interconnecting the lower ends of the tires  74   a ,  74   b.    
     When the horizontally spaced lights  70   a ,  70   b  of a higher luminance level are detected in the binarizing process, a quadrangular mask having a prescribed area and extending horizontally, which, for example, has a horizontal width greater than the horizontal width of the other vehicle Car, generally covering a distance from the left end of the light  70   a  to the right end of the light  70   b , and a vertical width slightly greater than the vertical width of the lights  70   a ,  70   b , is applied to the image of the other vehicle Car and vertically moved above the lights  70   a ,  70   b , and an area having a succession of identical pixel values within the grayscale image in the mask can be detected (extracted) as a roof (and a roof edge). Another quadrangular mask extending vertically, which, for example, has a horizontal width comparable to the horizontal width of the lights  70   a ,  70   b  and a vertical width which is 1 to 2 times the vertical width of the lights  70   a ,  70   b , is applied laterally of the lights  70   a ,  70   b , and an area having a succession of identical pixel values within the grayscale image in the mask can be detected (extracted) as a pillar (and a pillar edge) or a fender (and a fender edge). 
     The other vehicle Car thus detected has its lights  70   a ,  70   b  whose vertical height from the road surface  56  is within a height range that could possibly be detected in error as a head  50 . Therefore, the other vehicle Car is temporarily estimated as a pedestrian candidate PCY, and its image is stored as being labeled as run-length data, i.e., a labeling process is performed on its image in step S 3 . 
     At this time, the image thus processed is a large quadrangle-shaped image including a quadrangle circumscribing the pedestrian candidate PCY. If necessary, large quadrangle-shaped images including quadrangles circumscribing pedestrian candidates PCY are converted into images of one size in respective frames for easier image processing. 
     The processing of steps S 2 , S 3  is carried out by the pedestrian head candidate extractor  101 . The pedestrian head candidate extractor  101  (pedestrian head candidate extracting means, pedestrian head candidate extracting step) thus extracts a pedestrian candidate PCX (see  FIG. 4 ) including a head candidate  50  as a pedestrian head candidate, and a pedestrian candidate PCY (see  FIG. 5 ) including lights  70   a ,  70   b  as a pedestrian head candidate. 
     In step S 4 , the other vehicle determiner  103  which also functions as a target object determiner performs a target object determining process on the pedestrian candidate PCX ( FIG. 4 ) and the pedestrian candidate PCY ( FIG. 5 ) using the other vehicle candidate detector  102 , i.e., judges whether each of the pedestrian candidate PCX ( FIG. 4 ) and the pedestrian candidate PCY ( FIG. 5 ) is a pedestrian Pa that is actually walking or another vehicle Car. 
     In this case, by analyzing images that are successively acquired, the other vehicle determiner  103  determines the pedestrian candidate PCY as another vehicle Car because the pedestrian candidate PCY is actually a rigid body whose image remains unchanged in shape but changes in size only with time and whose image includes long straight edges (roof and fender), etc. 
     Actually, the other vehicle determiner  103  determines the shape of the other vehicle Car, i.e., judges whether it is a rigid body or not, by converting the image thereof into a circumscribed quadrangle of one size and analyzing the converted images. Since the shape of the image of the other vehicle Car remains unchanged, e.g., the distance between the lights  70   a ,  70   b  remains unchanged and the distance between the tires  74   a ,  74   b  remains unchanged, the other vehicle determiner  103  determines the pedestrian candidate PCY as a rigid body, i.e., another vehicle Car. 
     Actually, the other vehicle determiner  103  which functions as a target object determiner determines the pedestrian candidate PCX shown in  FIG. 4  as a pedestrian Pa when it detects that the horizontal width (width of the body  52 ) and height (height from the road surface  56  to the top of the head) of the pedestrian candidate PCX fall within a human range, and that the pedestrian candidate PCX is not a rigid body but an object which changes in shape. 
     As a result of the binarizing process in step S 2  and the labeling process in step S 3 , as shown in  FIG. 6 , a large high-luminance area  76  indicated by the thick solid lines may occasionally be detected on a pedestrian candidate PCYa. The high-luminance area  76  represents a combination (an area obtained by logical addition in binary images) of a heated area  78  indicated by the dot-and-dash lines and which represents a portion of the car body heated by heat-generating components such as the exhaust pipe  72  and the engine, a heated area representing the light  70   b , a heated area representing the exhaust pipe  72 , and a heated area representing the tire  74   b . In this case, the pedestrian candidate PCYa cannot be determined as another vehicle Car since it is difficult to detect the lights  70   a ,  70   b  as a pair of lights on account of the appearance of the high-luminance area  76 . 
     According to the present embodiment, when the pedestrian head candidate extractor  101  extracts the light  70   a  as a pedestrian candidate head in step S 3 , the other vehicle determiner  103  performs a process of determining the light  70   a  extracted as a pedestrian candidate head as part of the other vehicle Car if the other vehicle candidate detector  102  detects a high-luminance area  76  that is greater in area than the light  70   a  and has a horizontal length equal to or greater than a prescribed width, within a prescribed range (e.g., a range from the upper end of the lights  70   a ,  70   b  to the lower end of the tires  74   a ,  74   b ) beneath the horizontal position of the light  70   a , in the target object determining process in step S 4  which is performed by the other vehicle candidate detector  102  and the other vehicle determiner  103 . 
     Since the target object determining process is included, when the exhaust pipe  72  of a high-luminance area which is greater in area than the light  70   a  or  70   b  extracted as a pedestrian head candidate and has a horizontal length equal to or greater than a prescribed width, is detected within a prescribed range beneath the horizontal position of the light  70   a  or  70   b  on the pedestrian candidate PCY shown in  FIG. 5  which is free of the heated area  78 , the pedestrian candidate PCY can be detected as another vehicle Car. 
     As described above, the other vehicle determiner  103  (other vehicle determining means, other vehicle determining step) determines the light  70   a  extracted as a pedestrian candidate head from an image acquired by the infrared camera  16 , as part of the other vehicle Car if the other vehicle candidate detector  102  (other vehicle candidate detecting means, other vehicle candidate detecting step) detects a high-luminance area  76  (which may represent the exhaust pipe  72  only) that is greater in area than the light  70   a  and has a horizontal length equal to or greater than a prescribed width, within a prescribed range beneath the horizontal position of the light  70   a . Consequently, the other vehicle Car and the pedestrian Pa can be distinguished from each other highly accurately. 
     When the other vehicle candidate detector  102  detects the two lights  70   a ,  70   b  extracted as pedestrian head candidates on the pedestrian candidate PCY shown in  FIG. 5 , as another vehicle candidate, the other vehicle determiner  103  may determine the pedestrian candidate PCY as another vehicle Car based on the relationship between the two lights  70   a ,  70   b  and the exhaust pipe  72  which represents a high-luminance area. For example, the other vehicle determiner  103  may determine the pedestrian candidate PCY as another vehicle Car based on the positional relationship between the two lights  70   a ,  70   b  and the exhaust pipe  72  which represents a high-luminance area, or when a mask covering the two lights  70   a ,  70   b  is provided such that the mask extends toward the lower side of the two lights  70   a ,  70   b , and a high-luminance area which is greater than the areas of the lights  70   a ,  70   b  by a prescribed area or more is detected. 
     The other vehicle determiner  103  may also determine the pedestrian candidate PCY as another vehicle Car provided that the exhaust pipe  72  which represents a high-luminance area has a horizontal width (lateral width) Hwb that is smaller than the horizontal width (lateral width) Hwa of a region interconnecting the lights  70   a ,  70   b  detected as pedestrian head candidates. 
     Furthermore, when the other vehicle candidate detector  102  identifies or estimates (detects) an end  73  of the exhaust pipe  72 , i.e., a pipe end for emitting exhaust gas, as shown in  FIG. 5 , the other vehicle determiner  103  may determine the pedestrian candidate PCY as another vehicle Car based on the shape of a high-luminance area relevant to the end  73 , e.g., a shape considered to be correlated to a reference pattern (a reference pattern for the exhaust pipe  72 ) extending substantially concentrically outwardly from the end  73 . 
     In this case, when the other vehicle candidate detector  102  detects the lights  70   a ,  70   b  as pedestrian head candidates, in the quadrangle circumscribing the pedestrian candidate PCY which has been determined as a rigid body (an object which remains unchanged in shape with time) in the image shown in  FIG. 5 , the other vehicle determiner  103  may determine the pedestrian candidate PCY determined as the rigid body, as another vehicle Car. 
     When the other vehicle candidate detector  102  detects the exhaust pipe  72  as an exhaust pipe candidate of the engine and the tires  74   a ,  74   b  (horizontally spaced objects held in contact with the road surface  56 ) as tire candidates in the image shown in  FIG. 5 , the other vehicle determiner  103  may determine an object including the lights  70   a ,  70   b  as the pedestrian head candidates, as another vehicle Car. 
     If the other vehicle candidate detector  102  detects the light  70   a  and the exhaust pipe  72  as an exhaust pipe candidate of the engine or the tires  74   a ,  74   b  as tire candidates in the image shown in  FIG. 6 , then when the other vehicle candidate detector  102  detects a high-luminance area  76  that is greater than a prescribed area of the light  70   a  and that includes a heated area  78  which represents a portion of the car body heated by the exhaust pipe  72 , above the exhaust pipe  72  or the tires  74   a ,  74   b , the other vehicle determiner  103  may determine an object including the light  70   a  as the pedestrian head candidate and the high-luminance area  76  representing the exhaust pipe  72 , as another vehicle Car. In this case, when the other vehicle candidate detector  102  detects a high-luminance area  76  above the exhaust pipe  72  or the tires  74   a ,  74   b , it may be judged that an object including the light  70   a  as the pedestrian head candidate and the tires  74   a ,  74   b , as another vehicle Car. 
     According to another embodiment of the present invention, as shown in  FIG. 7 , when the other vehicle candidate detector  102  detects a pedestrian candidate PCYb having another high-luminance area  92   h  having a prescribed area or greater (representing, for example, a windshield of another car Car whose passenger compartment is warmed in a cold climate) or a low-luminance area  92   l  having a prescribed area or greater (representing, for example, a windshield of another car Car whose passenger compartment is cooled in a warm climate), above the light  70   a  and/or  70   b  as a pedestrian head candidate in the image, the other vehicle determiner  103  may determine the light  70   a  and/or  70   b  as part of the other vehicle Car regardless of whether the other vehicle candidate detector  102  detects the horizontal high luminance area  76 , the heated area  78  and the exhaust pipe  72 . 
     More specifically, if the temperature outside the vehicle is equal to or higher than a preset first temperature at which the passenger compartment needs to be cooled, then it is judged from a grayscale image, for example, whether or not there is a low-luminance area  92   l  which is greater in area than the light  70   a  or  70   b  above the light  70   a  and/or  70   b , and, if there is such a low-luminance area  92   l , it is determined that the light  70   a  and/or  70   b  is part of the other vehicle Car. If the temperature outside the vehicle is equal to or lower than a preset second temperature (lower than the first temperature) at which the passenger compartment needs to be warmed, then it is judged from a grayscale image, for example, whether or not there is a high-luminance area  92   h  which is greater in area than the light  70   a  or  70   b  above the light  70   a  and/or  70   b , and, if there is such a high-luminance area  92   h , it is determined that the light  70   a  and/or  70   b  is part of the other vehicle Car. 
     In this case, the temperature outside the vehicle can be detected based on the luminance of a grayscale image which corresponds to a temperature (prescribed temperature) of the head  50  which has been measured in advance. Alternatively, the temperature outside the vehicle may be detected by a temperature sensor (ambient air temperature sensor), not shown. 
     More specific details of the vehicle (other vehicle) determining process performed by the pedestrian head candidate extractor  101 , the other vehicle candidate detector  102  and the other vehicle determiner  103  will be described below with reference to  FIGS. 8A ,  8 B, and  9 .  FIGS. 8A and 8B  show another vehicle Cara which is different in shape from the other vehicle Car shown in  FIGS. 5 through 7 . 
       FIG. 8A  shows a present image Ipr and  FIG. 8B  shows a past image Ips. 
       FIG. 9  shows a table  90  of the horizontal and vertical coordinates of rectangular frames (see  FIGS. 8A and 8B ) in the present and past images Ipr, Ips, with their origin at the lower left end of each image. 
     The present and past images Ipr, Ips shown in  FIGS. 8A and 8B  include binarized high-luminance areas which are shown hatched. The high-luminance areas include an area representing a light  70   aa  extracted as a pedestrian head candidate, which is a heat source to be processed, and a high-luminance area  76   a  disposed beneath the light  70   aa  and greater in area than the light  70   aa  and which has a horizontal length equal to or greater than a prescribed width. In the images, only the light  70   aa  and the high-luminance area  76   a  have a luminance level “1” (white) brighter than the luminance threshold value for determining the human luminance level. 
     The other vehicle Cara is detected as a mask including coordinates A {(A1=xA1, yA1), (A0=xA0, yA0)} representing the coordinate center of a roof  80  which is a feature of the other vehicle Cara, a mask including coordinates L {(L1=xL1, yL1), (L0=xL0, yL0)} representing the coordinate center of a left fender (left pillar)  82 , and a mask including coordinates R {(R1=xR1, yR1), (R0=xR0, yR0)} representing the coordinate center of a right fender and including a high-luminance area  76   a.    
     As shown in  FIG. 9 , the coordinates R {(R1=xR1, yR1), (R0=xR0, yR0)}, the coordinates A {(A1=xA1, yA1), (A0=xA0, yA0)}, and the coordinates L {(L1=xL1, yL1), (L0=xL0, yL0)}, as well as coordinates T {(T1=xT1, yT1), (T0=xT0, yT0)} of a light  70   aa  as a pedestrian head candidate for comparing the present and past images Ipr, Ips, are calculated. 
     In this case, the following conditions  1 ,  2  are used as conditions for determining a vehicle. 
     However, even in a case where the conditions  1 ,  2  are satisfied, if the height H 1  of the light  70   aa  extracted as a pedestrian candidate on the present image Ipr from the road surface  56  (point of intersection with the road surface) is higher than the height H 0  of the light  70   aa  on the past image Ips, then since the light  70   aa  could possibly be a pedestrian head, a pedestrian candidate PCYc is not determined as another vehicle Cara under the conditions  1 ,  2  to be described below. 
     Condition 1: A polygon, i.e., a quadrangle  84  ( 84   pr ,  84   ps ), includes the light  70   aa  as a pedestrian head candidate and is formed by other masks, i.e., three masks including the coordinates R, A, L. If the past quadrangle  84   ps  and the present quadrangle  84   pr  are substantially similar to each other, then the pedestrian candidate PCYc is determined as the other car Cara, and recognized as either one of an approaching vehicle (including a vehicle at rest), a preceding vehicle followed by the driver&#39;s own vehicle, and a preceding vehicle moving apart from the driver&#39;s own vehicle (overtaking vehicle). 
     Condition 2: Present and past straight lines  86   pr ,  86   ps  are drawn between the light  70   aa  as a pedestrian head candidate and either one of the other masks, i.e., between the coordinates T (T1, T0) and the coordinates R (R1, R0) in  FIGS. 8A and 8B , and the length Lpr of the present straight line  86   pr  and the length Lps of the past straight line  86  ps are compared with each other. If Lps Lpr, i.e., if the length Lps of the past straight line  86  ps is equal to or greater than the length Lpr of the present straight line  86   pr , then the other vehicle Cara is recognized as a preceding vehicle followed by the driver&#39;s own vehicle or a preceding vehicle moving apart from the driver&#39;s own vehicle (overtaking vehicle). 
     After the target object determining process in step S 4  is finished, then the other vehicle determiner  103  judges whether each of the pedestrian candidates PCY ( FIG. 5 ), PCYa ( FIG. 6 ), PCYb ( FIG. 7 ), PCYc ( FIGS. 8A ,  8 B) is a pedestrian Pa shown in  FIG. 4  or not in step S 5 . If the other vehicle determiner  103  decides that the pedestrian candidate is determined as another vehicle Car, Cara, but not a pedestrian Pa, then it will be excluded from a subsequent processing sequence (S 5 : NO). 
     If the other vehicle determiner  103  decides that the pedestrian candidate is a pedestrian Pa shown in  FIG. 4  (S 5 : YES), then the contact possibility determiner  106  determines a contact possibility that the pedestrian Pa and the driver&#39;s own vehicle  12  will contact each other in step S 6 . 
     More specifically, the contact possibility determiner  106  determines a contact possibility in view of the period of time TTC according to the expression (1) and each motion vector of the pedestrian Pa (possibly also the distance Z), and also based on the brake depressed amount Br, the vehicle speed Vs, and the yaw rate Yr represented by the output signals respectively from the brake sensor  20 , the vehicle speed sensor  18 , and the yaw rate sensor  22 . If the contact possibility determiner  106  decides that the driver&#39;s own vehicle  12  will possibly contact the pedestrian Pa (S 6 : YES), then the attention seeking output generation determiner  108  generates an attention seeking output signal, thereby arousing attention of the driver, e.g., providing the driver with information, in step S 7 . More specifically, the attention seeking output generation determiner  108  highlights the pedestrian in the grayscale image on the HUD  26   a , with a surrounding frame in a bright color or the like, and produces a warning sound from the speaker  24 , thereby arousing attention of the driver of the vehicle  12 . 
     In this case, the attention seeking output generation determiner  108  highlights the pedestrian Pa in the grayscale image on the HUD  26   a , with a surrounding frame in a bright color such as red or yellow and generates an output for arousing the driver&#39;s attention. 
     The present invention is not limited to the above embodiment, but may adopt various arrangements based on the disclosure of the present description. 
     For example, as shown in  FIG. 10 , a vehicle periphery monitoring apparatus  10 A may include a pair of left and right infrared cameras  16 L,  16 R which are incorporated in a vehicle  12 A. The infrared cameras  16 L,  16 R, which are combined into a stereo camera system, are mounted in a front bumper of the vehicle  12 A at respective positions that are substantially symmetric with respect to a transversely central portion of the vehicle  12 A. The cameras  16 L,  16 R have respective optical axes parallel to each other and are located at equal heights from the road surface. The vehicle periphery monitoring apparatus which includes the left and right infrared cameras  16 L,  16 R handles a high-temperature area as a target object in left and right images of the periphery of the vehicle  12 A captured by the infrared cameras  16 R,  16 L, calculates the distance up to the target object according to the principles of triangulation based on the parallax of the target object in the left and right images, detects an object that is likely to affect the traveling of the vehicle (driver&#39;s own vehicle)  12 A, from the moving direction (motion vector) and position of the target object, and outputs an attention seeking output signal to seek attention of the driver of the vehicle  12 A. 
     While the invention has been particularly shown and described with reference to preferred embodiments, it will be understood that variations and modifications can be effected thereto by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.