Abstract:
An apparatus for monitoring the surroundings of a vehicle is provided with a second display unit that visually represents information on the presence of monitored objects by the display or lack of display of marks. When at least one monitored object is detected in a picked-up image, the marks are displayed in different forms in accordance with the hazard the monitored object poses to the vehicle.

Description:
TECHNICAL FIELD 
       [0001]    The present invention relates to a vehicle periphery monitoring apparatus (apparatus for monitoring surroundings of vehicle) for detecting a monitored target in the periphery of a vehicle and for displaying the detected object in a simple format. 
       BACKGROUND ART 
       [0002]    There has heretofore been known a vehicle periphery monitoring apparatus for displaying an image captured of an area in front of a vehicle by an infrared camera. The image is displayed on a display in front of the driver&#39;s seat, and in the image, an area is highlighted representing a pedestrian detected from the image (see FIG. 5 of Japanese Laid-Open Patent Publication No. 2009-067214). 
         [0003]    Another known apparatus displays an icon indicating the presence of a pedestrian on a head-up display (HUD) in addition to displaying a highlighted image area representing a pedestrian in an image displayed on a display. According to Japanese Laid-Open Patent Publication No. 2004-364112, if a pedestrian is determined to be present in an image captured by an infrared camera, an icon of the pedestrian is displayed on an HUD (see FIG. 6 and paragraphs [0036] through [0038]). 
         [0004]    One technology for detecting pedestrians is capable of dealing with both processing speed and judging accuracy, by simply selecting a pedestrian candidate from binarized information and judging if the candidate represents a pedestrian based on grayscale information (see Abstract of Japanese Laid-Open Patent Publication No. 2003-284057). 
       SUMMARY OF INVENTION 
       [0005]    According to Japanese Laid-Open Patent Publication No. 2004-364112, as described above, an icon indicating the presence of a pedestrian is displayed on an HUD. However, much remains to be improved in relation to calling more appropriate attention from the user. 
         [0006]    The present invention has been made in view of the above task. It is an object of the present invention to provide a vehicle periphery monitoring apparatus, which is capable of calling appropriate attention from the user. 
         [0007]    According to the present invention, there is provided a vehicle periphery monitoring apparatus for detecting a monitored target in the periphery of a vehicle based on a captured image signal generated by an image capturing device mounted on the vehicle, comprising a first display unit that displays a captured image represented by the captured image signal, a second display unit that visualizes information concerning whether or not the monitored target exists in a plurality of sub-regions, which make up the captured image displayed on the first display unit, based on whether marks associated respectively with the sub-regions are displayed, and an attention degree evaluator that evaluates a degree of attention of the monitored target for the vehicle, if at least one instance of the monitored target is detected in the captured image, wherein the second display unit displays the marks in different display modes depending on the degree of attention evaluated by the attention degree evaluator. 
         [0008]    According to the present invention, if at least one instance of the monitored target is detected in the captured image, the second display unit displays the marks in different display modes depending on the degree of attention of the monitored target for the vehicle. Accordingly, it is possible to visually indicate to the user different degrees of attention of monitored targets, thereby calling appropriate attention from the user. 
         [0009]    The degree of attention may represent a misidentifying possibility that the driver or occupant of the vehicle may possibly misidentify the position of the monitored target by visually recognizing the mark that is displayed. If it is judged that the misidentifying possibility is high, then the second display unit may simultaneously or alternately display the marks corresponding to one of the sub-regions in which at least a portion of the monitored target exists and an adjacent one of the sub-regions. The existence of the monitored target is thus displayed in a highlighted manner, making it possible to call appropriate attention from the user. 
         [0010]    The attention degree evaluator may judge that the misidentifying possibility is high if the monitored target exists on one of boundary lines between the sub-regions. 
         [0011]    The attention degree evaluator may judge that the misidentifying possibility is high before or after the monitored target moves across one of boundary lines between the sub-regions. 
         [0012]    The attention degree evaluator may judge that the degree of attention is high if the monitored target is highly likely to collide with the vehicle. 
         [0013]    The degree of attention may represent a possibility of collision of the monitored target with the vehicle. In this case, the attention degree evaluator may evaluate the possibility of collision of each monitored target if the monitored targets are detected respectively in at least two of the sub-regions, and the second display unit may display the marks in different display modes depending on the possibility of collision. Consequently, the difference between the degrees of attention of the monitored targets can be indicated to the user for assisting in driving the vehicle. 
         [0014]    The second display unit may display one of the marks depending on at least one monitored target whose possibility of collision is evaluated as being high, so as to be more visually highlighted than another one of the marks depending on another one of the monitored targets. Thus, the existence of a monitored target whose attention level is relatively high from among a plurality of monitored targets can be conveniently indicated to the driver. 
         [0015]    The attention degree evaluator may judge whether or not it is easy for the driver of the vehicle to locate the monitored target based on at least the captured image signal, and evaluate the possibility of collision depending on the result of the judgment. Accordingly, the accuracy in evaluating the degree of risk is increased by also taking into account an evaluation considered from the viewpoint of the driver. 
         [0016]    The attention degree evaluator may judge whether or not the monitored target recognizes the existence of the vehicle based on at least the captured image signal, and evaluate the possibility of collision depending on the result of the judgment. Thus, the accuracy in evaluating the degree of risk can be increased by also taking into account an evaluation considered from the viewpoint of the monitored target. 
         [0017]    The attention degree evaluator may predict a route to be followed by the vehicle, and evaluate the possibility of collision depending on the predicted route. Accordingly, the accuracy in evaluating the degree of risk can be increased by also taking into account the predicted route to be followed by the vehicle. 
         [0018]    The attention degree evaluator may predict a direction of travel of the monitored target, and evaluate the possibility of collision depending on the predicted direction of travel. Accordingly, the accuracy in evaluating the degree of risk can be increased by also taking into account the direction of travel of the monitored target. 
         [0019]    The sub-regions may comprise a central region corresponding to a central range that includes a direction of travel of the vehicle, a left region corresponding to a left range that is positioned to the left of the central range, and a right region corresponding to a right range that is positioned to the right of the central range, in an image range captured in front of the vehicle by the image capturing device. Therefore, apart from monitored targets that exist on left and right sides of the direction of travel of the vehicle, it is possible to call attention from the driver concerning a monitored target that exists in the direction of travel of the vehicle and is likely to collide with the vehicle. 
         [0020]    The vehicle periphery monitoring apparatus may further comprise a region selector that selects one of the sub-regions to which a target image area sought as an image area of the monitored target from the captured image belongs. The region selector may select the central region if the target image area is positioned on a boundary line between the central region and the left region, or is positioned on a boundary line between the central region and the right region. 
         [0021]    Generally, when a monitored target exists in the central range including the direction of travel of the vehicle, the driver pays more attention to the monitored target than if the monitored target were to exist in the left and right ranges. According to the present invention, if a target image area exists over a range between the central region and the left or right region i.e., on one of the boundary lines of the central region, the monitored target is detected as belonging to the central range, rather than the left range or the right range. Therefore, the driver is made to pay as much attention to the detected monitored target as attention that would be directed to a monitored target included fully within the central range. 
         [0022]    The vehicle periphery monitoring apparatus may further comprise a direction-of-turn detecting sensor that detects a direction of turn of the vehicle, and a boundary line setter that displaces the boundary line between the central region and the right region toward the right region if the direction-of-turn detecting sensor detects a left turn of the vehicle, and displaces the boundary line between the central region and the left region toward the left region if the direction-of-turn detecting sensor detects a right turn of the vehicle. 
         [0023]    A horizontal distance between a monitored target that exists near an edge of a road and the vehicle tends to be greater when the vehicle is traveling on a curved road than when the vehicle is traveling on a straight road. Thus, while the vehicle is making a left turn, the boundary line setter displaces the boundary line between the central region and the right region toward the right region. Similarly, while the vehicle is making a right turn, the boundary line setter displaces the boundary line between the central region and the left region toward the left region. In this manner, an image area of the monitored target existing near the edge of the road is displayed on the second display unit as belonging to the central region, thereby drawing attention from the driver to the monitored target. 
         [0024]    The vehicle periphery monitoring apparatus may further comprise a vehicle speed sensor that detects a vehicle speed of the vehicle, and a boundary line setter that displaces the boundary line between the central region and the right region toward the right region and displaces the boundary line between the central region and the left region toward the left region, if the vehicle speed detected by the vehicle speed sensor is high rather than low. 
         [0025]    At times that the vehicle is traveling at high speed, the time required for the vehicle to approach a monitored target in front of the vehicle is shorter than if the vehicle were traveling at low speed, so that the driver needs to pay more attention to the monitored target. Accordingly, while the vehicle is traveling at high speed, the boundary line setter displaces the boundary line between the central region and the left region toward the left region, and displaces the boundary line between the central region and the right region toward the right region. Consequently, a target image area, which would be displayed as belonging to the left region or the right region on the second display unit while the vehicle is traveling at low speed, is displayed as belonging to the central region while the vehicle is traveling at high speed. Consequently, while the vehicle is traveling at high speed, early attention can be called from the driver concerning the monitored target that is approaching the vehicle. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0026]      FIG. 1  is a block diagram showing the arrangement of a vehicle periphery monitoring apparatus according to a first embodiment of the present invention; 
           [0027]      FIG. 2  is a perspective view of a vehicle incorporating the vehicle periphery monitoring apparatus shown in  FIG. 1 ; 
           [0028]      FIG. 3  is a view showing a scene as viewed from the driver of the vehicle shown in  FIG. 2 ; 
           [0029]      FIG. 4  is a view showing by way of example a displayed screen on a general-purpose monitor; 
           [0030]      FIG. 5  is a view showing by way of example a displayed screen on an MID (Multi-Information Display); 
           [0031]      FIG. 6  is a view showing the relationship between displayed images on the general-purpose monitor and the MID; 
           [0032]      FIG. 7  is a flowchart of a general operation sequence of the vehicle periphery monitoring apparatus shown in  FIG. 1 ; 
           [0033]      FIG. 8  is a view showing by way of example a positional relationship between the vehicle and a biological target, an example of a grayscale image displayed on the general-purpose monitor, and an example of an icon image displayed on the MID, at a time that the biological target is far from the vehicle; 
           [0034]      FIG. 9  is a view showing by way of example a positional relationship between the vehicle and a biological target, an example of a grayscale image displayed on the general-purpose monitor, and an example of an icon image displayed on the MID, at a time that the biological target is close to the vehicle; 
           [0035]      FIG. 10  is a view showing by way of example a positional relationship between the vehicle and a biological target, an example of a grayscale image displayed on the general-purpose monitor, and an example of an icon image displayed on the MID, at a time that the vehicle is traveling at low speed; 
           [0036]      FIG. 11  is a view showing by way of example a positional relationship between the vehicle and a biological target, an example of a grayscale image displayed on the general-purpose monitor, and an example of an icon image displayed on the MID, at a time that the vehicle is traveling at high speed; 
           [0037]      FIG. 12  is a view showing a relationship between displayed images on the general-purpose monitor and the MID; 
           [0038]      FIGS. 13A and 13B  are views, each of which shows by way of example a positional relationship between the vehicle and a biological target, an example of an image displayed on the general-purpose monitor, and an example of an icon image displayed on the MID; 
           [0039]      FIG. 14  is a flowchart of a processing sequence for segmenting a captured image depending on a turn made by the vehicle; 
           [0040]      FIGS. 15A through 15C  are views illustrating advantages of a segmentation process, which is performed when the vehicle makes a turn; 
           [0041]      FIG. 16  is a flowchart of a processing sequence for segmenting a captured image depending on the speed of the vehicle; 
           [0042]      FIGS. 17A and 17B  are views illustrating advantages of a segmentation process, which is performed depending on the speed of the vehicle; 
           [0043]      FIG. 18  is a block diagram showing the arrangement of a vehicle periphery monitoring apparatus according to a second embodiment of the present invention; 
           [0044]      FIG. 19A  is a front elevational view of a general-purpose monitor; 
           [0045]      FIG. 19B  is a front elevational view of an MID; 
           [0046]      FIG. 20  is a flowchart of a general operation sequence of the vehicle periphery monitoring apparatus shown in  FIG. 18 ; 
           [0047]      FIGS. 21A and 21B  are views showing by way of example first images captured by an infrared camera; 
           [0048]      FIG. 22  is a view showing a corresponding relationship between a first position in a first display region and a second position in a second display region; 
           [0049]      FIG. 23  is a view showing by way of example images displayed respectively on the general-purpose monitor and the MID as representing information concerning the first image shown in  FIG. 21A ; 
           [0050]      FIG. 24  is a detailed flowchart of step S 37  shown in  FIG. 20 ; 
           [0051]      FIGS. 25A through 25C  are views illustrating a process of evaluating a degree of risk from the direction along which a monitored target moves; 
           [0052]      FIGS. 26A and 26B  are views illustrating a process of evaluating a degree of risk from a predicted route to be followed by the vehicle; and 
           [0053]      FIG. 27  is a view showing by way of example images displayed respectively on the general-purpose monitor and the MID, wherein the images represent information concerning the first image shown in  FIG. 21B . 
       
    
    
     DESCRIPTION OF EMBODIMENTS 
       [0054]    Vehicle periphery monitoring apparatus according to preferred embodiments of the present invention will be described below with reference to the accompanying drawings. More specifically, a vehicle periphery monitoring apparatus according to a first embodiment of the present invention will be described below with reference to  FIGS. 1 through 11 , a modification thereof will be described below with reference to  FIGS. 12 through 17B , and a vehicle periphery monitoring apparatus according to a second embodiment of the present invention will be described below with reference to  FIGS. 18 through 27 . 
       A. First Embodiment 
     [1. Arrangement] 
     (1-1. Overall Arrangement) 
       [0055]      FIG. 1  is a block diagram showing an arrangement of a vehicle periphery monitoring apparatus  10  according to a first embodiment of the present invention.  FIG. 2  is a perspective view of a vehicle  12  that incorporates the vehicle periphery monitoring apparatus  10  therein.  FIG. 3  is a view showing a scene as viewed from the perspective of a driver or a user of the vehicle  12 .  FIG. 3  shows a situation in which the vehicle  12  is travelling on a road, in a country that requires all vehicles to keep to the right side of the road. The vehicle  12  is illustrated as a left-hand drive car. However, the same arrangement as the illustrated arrangement may be employed in right-hand drive cars. 
         [0056]    As shown in  FIGS. 1 and 2 , the vehicle periphery monitoring apparatus  10  includes left and right infrared cameras  16 L,  16 R, a vehicle speed sensor  18 , a yaw rate sensor  20  (direction-of-turn detecting sensor), an electronic control unit  22  (hereinafter referred to as an “ECU  22 ”), a speaker  24 , a general-purpose monitor  26  (first display unit), and an MID  28  (Multi-Information Display, also referred to as a second display unit). 
       (1-2. Infrared Cameras  16 L,  16 R) 
       [0057]    The infrared cameras  16 L,  16 R are image capturing devices, which function as image capturing means for capturing images of the periphery of the vehicle  12 . According to the present embodiment, the two infrared cameras  16 L,  16 R are combined to make up a stereo camera. The infrared cameras  16 L,  16 R both have a characteristic such that, as the temperature of a subject is higher, output signals from the infrared cameras  16 L,  16 R become higher in level (increase in brightness). 
         [0058]    As shown in  FIG. 2 , the infrared cameras  16 L,  16 R are disposed on the front bumper of the vehicle  12 , at respective positions symmetric with respect to the transverse center of the vehicle  12 . The two infrared cameras  16 L,  16 R have respective optical axes, which lie parallel to each other and are fixed at equal heights from the surface of the road. 
       (1-3. Vehicle Speed Sensor  18  and Yaw Rate Sensor  20 ) 
       [0059]    The vehicle speed sensor  18  detects a vehicle speed V [km/h] of the vehicle  12 , and supplies an output signal representing the detected vehicle speed V to the ECU  22 . The yaw rate sensor  20  detects a yaw rate Yr [°/sec] of the vehicle  12 , and supplies an output signal representing the detected yaw rate Yr to the ECU  22 . 
       (1-4. ECU  22 ) 
       [0060]    The ECU  22  serves as a controller for controlling the vehicle periphery monitoring apparatus  10 . As shown in  FIG. 1 , the ECU  22  includes an input/output unit  30 , a processor  32 , and a memory  34 . 
         [0061]    Signals from the infrared cameras  16 L,  16 R, the vehicle speed sensor  18 , and the yaw rate sensor  20  are supplied through the input/output unit  30  to the ECU  22 . Output signals from the ECU  22  are supplied through the input/output unit  30  to the speaker  24 , the general-purpose monitor  26 , and the MID  28 . The input/output unit  30  has an A/D converter circuit, not shown, which converts analog signals supplied thereto into digital signals. 
         [0062]    The processor  32  performs processing operations on the signals from the infrared cameras  16 L,  16 R, the vehicle speed sensor  18 , and the yaw rate sensor  20 . Based on the results of such processing operations, the processor  32  generates signals to be supplied to the speaker  24 , the general-purpose monitor  26 , and the MID  28 . 
         [0063]    As shown in  FIG. 1 , the processor  32  includes a binarizing function  40 , a biological target extracting function  42 , an attention degree evaluating function  44  (attention degree evaluator), a speaker controlling function  45 , a general-purpose monitor controlling function  46 , and an MID controlling function  48 . These functions  40 ,  42 ,  44 ,  45 ,  46 ,  48  are performed upon execution of programs stored in the memory  34 . Alternatively, the programs may be supplied from an external source through a non-illustrated wireless communication device (a cell phone, a smart phone, or the like). 
         [0064]    The binarizing function  40  generates a binarized image (not shown) by binarizing a grayscale image  72  ( FIG. 4 ), which is acquired by one of the infrared cameras  16 L,  16 R (the left infrared camera  16 L in the present embodiment). Using the grayscale image  72  and the binarized image, the biological target extracting function  42  extracts a biological target (hereinafter referred to as a “monitored target” or simply “a target”) such as a human being or an animal that is present in the images. When at least one biological target is detected, the degree of attention evaluating function  44  evaluates a degree of attention of the detected biological target for the vehicle  12 . The speaker controlling function  45  controls the speaker  24  to produce a warning sound or the like. The general-purpose monitor controlling function  46  controls the general-purpose monitor  26  to display the grayscale image  72 . 
         [0065]    The MID controlling function  48  controls the MID  28  in order to display a mark, e.g., an icon (hereinafter referred to as a “biological target icon”) representing a biological target such as a human being or an animal on the MID  28 . As shown in  FIG. 1 , the MID controlling function  48  includes a boundary line setting function  50  (boundary line setter), a sub-region selecting function  52  (region selector), and an icon displaying function  54 . Details of such functions  50 ,  52 ,  54  will be described later. 
         [0066]    The memory  34  includes a RAM (Random Access Memory) for storing temporary data, etc., used for various processing operations, and a ROM (Read Only Memory) for storing programs to be executed, tables, maps, etc. 
       (1-5. Speaker  24 ) 
       [0067]    The speaker  24  produces a warning sound or the like based on a command from the ECU  22 . Although not shown in  FIG. 3 , the speaker  24  is mounted on a dashboard  60  ( FIG. 3 ) of the vehicle. A speaker belonging to an audio system, not shown, or a navigation system, not shown, may alternatively be used as the speaker  24 . 
       (1-6. General-Purpose Monitor  26 ) 
       [0068]    The general-purpose monitor  26  comprises a liquid crystal panel, an organic EL (ElectroLuminescence) panel, or an inorganic EL panel for displaying color or monochromatic images. As shown in  FIGS. 2 and 3 , the general-purpose monitor  26  is mounted in a given position on the dashboard  60 , and more specifically, in a position on the right-hand side of the steering wheel  64 . 
         [0069]      FIG. 4  is a view showing by way of example a screen that is displayed on the general-purpose monitor  26 . As shown in  FIG. 4 , the general-purpose monitor  26  includes a display region  70  (hereinafter referred to as a “first display region  70 ” or a “display region  70 ”), which displays a grayscale image  72  captured by the left infrared camera  16 L. 
         [0070]    The general-purpose monitor  26  can add a highlighting feature, which is generated by the general-purpose monitor controlling function  46 , to the grayscale image  72 . More specifically, as shown in  FIG. 4 , the general-purpose monitor  26  displays a highlighting frame  76  around an image area  74 , which represents an extracted biological target such as a human being or an animal (target image area, hereinafter referred to as a “biological area  74 ”). Alternatively, the general-purpose monitor  26  may apply a color to the biological area  74 , or may display the highlighting frame  76  in addition to applying a color to the biological area  74 , or may highlight the biological area  74  in another way. 
         [0071]    The general-purpose monitor  26  may display a grayscale image  72  captured by the right infrared camera  16 R, rather than the grayscale image  72  captured by the left infrared camera  16 L. The general-purpose monitor  26  may also display any of various other images, including navigation images such as road maps, service information, etc., or moving image content, etc., simultaneously in addition to, or selectively instead of the grayscale image  72  from the infrared camera  16 L or the infrared camera  16 R. The general-purpose monitor  26  may select any of such images in response to pressing of a certain pushbutton switch, or according to a preset selecting condition, for example. 
       (1-7. MID  28 ) 
       [0072]    The MID  28  is a simple display device (icon display device) for visualizing and displaying ancillary information at the time that the vehicle  12  is driven. The MID  28  comprises a display module, which is simpler in structure and less costly than the general-purpose monitor  26 , particularly the display panel thereof. For example, a display panel, which is lower in resolution than the general-purpose monitor  26 , e.g., a display panel that operates in a non-interlace mode, may be used as the MID  28 . 
         [0073]    As shown in  FIGS. 2 and 3 , the MID  28  is mounted on the dashboard  60  upwardly of and proximate an instrument panel  62 , or is mounted directly on the instrument panel  62 . The MID  28  is disposed in a position that enables the driver of the vehicle  12  to see the MID  28  through an upper gap in the steering wheel  64 . Therefore, the driver can observe the MID  28  while the driver&#39;s face is oriented toward the front of the vehicle  12 . 
         [0074]      FIG. 5  is a view showing by way of example a displayed screen on the MID  28 . As shown in  FIG. 5 , the MID  28  has a display region  80  (hereinafter referred to as a “second display region  80 ” or a “display region  80 ”), which displays an image  82  made up of various icons (hereinafter referred to as an “icon image  82 ”) corresponding to the grayscale image  72 . 
         [0075]    For example, as shown in  FIG. 5 , the display region  80  displays in a lower portion thereof a road icon  84 , which indicates a road along the direction of travel of the vehicle  12 . The road icon  84  is made up of three lines, i.e., lines  84 L,  84 C,  84 R, arranged successively from the left. A width of a gap between the lines  84 L,  84 R becomes progressively smaller toward the upper end in the display region  80 , which is suggestive of a remote position. The displayed road icon  84  allows the driver to visualize the shape of a front road, typically a straight road, as the road is observed from the perspective of the driver&#39;s seat in the vehicle  12 . 
         [0076]    As shown in  FIG. 5 , the display region  80  can display in an upper portion thereof a human icon  86  representing a pedestrian who is present in the periphery of the vehicle  12 . According to the present embodiment, the human icon  86  can be displayed at three locations, i.e., left, central, and right locations, in the display region  80  (see  FIGS. 6 and 8 ). 
         [0077]    Incidentally, instead of the human icon  86 , icons representing other biological target (e.g., an animal icon representing an animal) may be displayed. 
         [0078]    Alternatively, instead of the icons referred to above, i.e., the road icon  84 , the human icon  86 , and the animal icon, the MID  28  may selectively display information concerning the mileage of the vehicle  12 , the present time, and the instrument panel  62 . The MID  28  may select any of such items of information (images) in response to pressing of a certain pushbutton switch, or according to a preset selecting condition, for example. 
       [2. Relationship Between Images Displayed on the General-Purpose Monitor  26  and the MID  28 ] 
       [0079]      FIG. 6  is a view showing a relationship between images displayed respectively on the general-purpose monitor  26  and the MID  28 . As shown in  FIG. 6 , according to the present embodiment, the grayscale image  72  is segmented into three regions (hereinafter referred to as “first sub-regions  90 L,  90 C,  90 R” and referred to collectively as “first sub-regions  90 ”), which are arrayed along the transverse direction of the vehicle  12 . Boundary lines between the first sub-regions  90  (hereinafter referred to as “first boundary lines  92 L,  92 R” and referred to collectively as “first boundary lines  92 ”) are imaginary lines, which are not included in the actual grayscale image  72 , and are fixed and remain unchanged. In an actual processing operation, only positional information of the first boundary lines  92  may be used, whereas positional information of the first sub-regions  90  may not be used. The first boundary lines  92  may be shaped as an inverted chevron along road lanes, similar to the road icon  84  shown on the MID  28 . 
         [0080]    As shown in  FIG. 6 , the icon image  82  is segmented into three regions (hereinafter referred to as “second sub-regions  100 L,  100 C,  100 R” and referred to collectively as “second sub-regions  100 ”) arrayed along the transverse direction of the vehicle  12 . Boundary lines between the second sub-regions  100  in the icon image  82  (hereinafter referred to as “second boundary lines  102 L,  102 R” and referred to collectively as “second boundary lines  102 ”) are imaginary lines, which are not included in the actual icon image  82 , and are fixed and remain unchanged. The second boundary lines  102 L,  102 R are associated respectively with the first boundary lines  92 L,  92 R. As with the first boundary lines  92 , the second boundary lines  102  may be shaped in an upwardly tapered manner along road lanes, similar to the road icon  84  shown on the MID  28 . 
         [0081]    According to the present embodiment, one of the first sub-regions  90  to which the biological area  74  belongs (hereinafter referred to as a “first biological area existing sub-region”) in the grayscale image  72  is determined, and a biological icon, such as a human icon  86 , an animal icon, or the like, is displayed on the MID  28  in one of the second sub-regions  100  of the icon image  82 , which corresponds to the biological area existing sub-region (hereinafter referred to as a “second biological area existing sub-region”). Stated otherwise, depending on whether or not marks (a human icon  86  or the like) associated respectively with the first sub-regions  90  of the grayscale image  72  are displayed on the general-purpose monitor  26 , information is visualized concerning whether or not monitored targets (biological targets) exist in the first sub-regions  90  of the grayscale image  72 . In certain cases, as described in detail later, the number of biological icons to be displayed increases from 1 to 2. 
       [3. Operations of Vehicle Periphery Monitoring Apparatus  10 ] 
       [0082]      FIG. 7  is a flowchart of a general operation sequence of the vehicle periphery monitoring apparatus  10 . In step S 1  of  FIG. 7 , the infrared cameras  16 L,  16 R capture images of the periphery of the vehicle  12 . In step S 2 , the ECU  22  converts analog signals from the infrared cameras  16 L,  16 R into digital signals, so as to acquire a grayscale image  72 . In step S 3 , the ECU  22  performs a binarizing process. In the binarizing process, the ECU  22  binarizes the grayscale image  72  into a non-illustrated binarized image. 
         [0083]    In step S 4 , the ECU  22  extracts a biological area  74  from the acquired binarized image and the grayscale image  72 . Since a biological target is higher in temperature than the surrounding area, the area corresponding to the biological target, i.e., the biological area  74 , appears high in brightness in the binarized image and in the grayscale image  72 . Consequently, it is possible to extract a biological area  74  by searching the binarized image and the grayscale image  72  for an area of pixels having a brightness level that is greater than a predetermined threshold value. 
         [0084]    Both the binarized image and the grayscale image  72  are used in order to identify the presence of a biological target easily from the binarized image, and then acquire detailed information concerning the biological target from the grayscale image  72 . Such a processing sequence is disclosed in Japanese Laid-Open Patent Publication No. 2003-284057, for example. Alternatively, a biological area  74  may be extracted from either one of the binarized image and the grayscale image  72 . 
         [0085]    In step S 5 , the ECU  22  displays the grayscale image  72  with the highlighted biological area  74  on the general-purpose monitor  26 . As described above, the ECU  22  highlights the biological area  74  with at least one of a color applied to the biological area  74  and the highlighting frame  76  added around the biological area  74  ( FIG. 4 ). 
         [0086]    In step S 6 , the ECU  22  establishes first boundary lines  92  ( FIG. 6 ) in the grayscale image  72  or the binarized image, thereby segmenting the grayscale image  72  or the binarized image into first sub-regions  90 . More specifically, the ECU  22  establishes first boundary lines  92  in order to segment the grayscale image  72  or the binarized image into three equal first sub-regions  90  arranged along the transverse direction of the vehicle  12 . 
         [0087]    In step S 7 , the ECU  22  determines one of the first sub-regions  90  to which the biological area  74  belongs (first biological area existing sub-region). If the biological area  74  exists on one of the first boundary lines  92 , then the ECU  22  may determine two first sub-regions  90  on both sides of the first boundary line  92  as first sub-regions  90  to which the biological area  74  belongs. 
         [0088]      FIGS. 8 through 11  are views illustrating processes of identifying a first sub-region  90  to which the biological area  74  belongs (first biological area existing sub-region). More specifically,  FIG. 8  shows the positional relationship between the vehicle  12  and a person  110 , together with an example of the grayscale image  72  that is displayed on the general-purpose monitor  26  and an example of the icon image  82  that is displayed on the MID  28  when the person  110  is located far from the vehicle  12 .  FIG. 9  shows the positional relationship between the vehicle  12  and a person  110 , together with an example of the grayscale image  72  that is displayed on the general-purpose monitor  26  and an example of the icon image  82  that is displayed on the MID  28  when the person  110  is located close to the vehicle  12 .  FIG. 10  shows the positional relationship between the vehicle  12  and a person  110 , together with an example of the grayscale image  72  that is displayed on the general-purpose monitor  26  and an example of the icon image  82  that is displayed on the MID  28  when the vehicle speed V is low, i.e., when the vehicle  12  is traveling at low speed.  FIG. 11  shows the positional relationship between the vehicle  12  and a person  110 , together with an example of the grayscale image  72  that is displayed on the general-purpose monitor  26  and an example of the icon image  82  that is displayed on the MID  28  when the vehicle speed V is high, i.e., when the vehicle  12  is traveling at high speed. In  FIGS. 8 through 11 , α represents an angle of view of the infrared camera  16 L. 
         [0089]    As shown in  FIG. 8 , when the person  110  is far from the vehicle  12  and the person  110  (biological area  74 ) exists on one of the first boundary lines  92 L, a biological icon (human icon  86 ) is displayed at one location on the MID  28 . On the other hand, as shown in  FIG. 9 , when the person  110  is close to the vehicle  12  and the person  110  (biological area  74 ) exists on one of the first boundary lines  92 L, a biological icon (human icon  86 ) is displayed at two locations on the MID  28 , thereby indicating the person  110  in a highlighted manner to the driver. 
         [0090]    As shown in  FIG. 10 , when the vehicle speed V is low and the person  110  (biological area  74 ) exists on one of the first boundary lines  92 L, a biological icon (human icon  86 ) is displayed at one location on the MID  28 . On the other hand, as shown in  FIG. 11 , when the vehicle speed V is high and the person  110  (biological area  74 ) exists on one of the first boundary lines  92 L, a biological icon (human icon  86 ) is displayed at two locations on the MID  28 , thereby indicating the person  110  in a highlighted manner to the driver. In the example illustrated in  FIG. 11 , the MID  28  displays a plurality of biological icons simultaneously. However, the MID  28  may also display the plurality of biological icons (human icons  86  or the like) in an alternating manner. 
         [0091]    In step S 8 , the ECU  22  determines one of the second sub-regions  100  (a second biological area existing sub-region), which corresponds to the first biological area existing sub-region. 
         [0092]    In step S 9 , the ECU  22  displays a biological target (a human icon  86  or the like) representing the biological target in the second biological area existing sub-region, which was determined in step S 8 . If there is a high likelihood of collision between the vehicle  12  and the biological target, then the speaker  24  may generate a warning sound. 
       [4. Supplementary Remarks] 
       [0093]    In the above embodiment, it is determined whether or not the biological area  74  exists on one of the first boundary lines  92  based on the position of the biological area  74  at the present time (in a present processing cycle). However, the judgment process is not limited to this technique. It is possible to regard a first sub-region  90  in which the person  110  (biological area  74 ) is highly likely to move as a first biological area existing sub-region, based on a motion vector of the person  110  (biological area  74 ) or the position thereof in the grayscale image  72 , thereby calling more appropriate attention from the driver. 
         [0094]    Upon use of the motion vector of the biological area  74 , if the biological area  74  exists in the central first sub-region  90 C and the motion vector is directed to the left, then the central first sub-region  90 C and the left first sub-region  90 L are selected. On the other hand, if the biological area  74  exists in the central first sub-region  90 C and the motion vector is directed to the right, then the central first sub-region  90 C and the right first sub-region  90 R are selected. 
         [0095]    Upon use of the position of the biological area  74  on the grayscale image  72 , if the biological area  74  exists in a left side of the central first sub-region  90 C, then the central first sub-region  90 C and the left first sub-region  90 L are selected. On the other hand, if the biological area  74  exists in a right side of the central first sub-region  90 C, then the central first sub-region  90 C and the right first sub-region  90 R are selected. 
         [0096]    The motion vector and the position on the grayscale image  72  may also be used to correct the position of the biological area  74 , which is used in the process involving the first boundary lines  92 , and the process carried out when there is a high possibility of collision between the vehicle  12  and the biological target. For example, if the motion vector of the biological area  74  is directed to the left, then using coordinates that are shifted to the left from the position (present position) where the biological area  74  exists, it may be judged whether or not the biological area  74  exists on one of the first boundary lines  92 . 
       [5. Advantages] 
       [0097]    As described above, the degree of attention evaluating function  44  evaluates the degree of attention of a biological target for the vehicle  12  if at least one biological target (a monitored target such as a person  110  or an animal  160 ) is detected in the first sub-regions  90  of the grayscale image  72 , and the MID  28  displays a mark in a different display mode depending on the degree of attention evaluated by the degree of attention evaluating function  44 . Accordingly, it is possible to visually indicate to the user different degrees of attention of monitored targets, thereby calling appropriate attention from the user. 
         [0098]    According to the first embodiment, the degree of attention represents a misidentifying possibility that the driver or occupant of the vehicle  12  may possibly misidentify the position of the monitored target such as the person  110  or the like by visually recognizing the displayed mark. If it is judged that the misidentifying possibility is high, then a plurality of biological icons (human icons  86 ) corresponding to one of the first sub-regions  90  where at least a portion of the monitored target exists and an adjacent one of the first sub-regions  90  are displayed simultaneously on the MID  28 . 
         [0099]    If the possibility of misidentification is high, this implies that (1) the biological area  74  exists on one of the first boundary lines  92 , (2) the biological area  74  lies across one of the first boundary lines  92 , or (3) the person  110  is highly likely to collide with the vehicle  12  (e.g., the person  110  is close to the vehicle  12  or the vehicle speed V is high). 
       B. Modification of First Embodiment 
       [0100]    A modification of the operation sequence of the vehicle periphery monitoring apparatus  10  will be described below. Such a modification differs from the first embodiment in relation to the behavior of the boundary line setting function  50  (step S 6  of  FIG. 7 ). Details of this modification will be described below with reference to  FIGS. 12 through 17B . According to the modification, it is assumed that the vehicle  12  travels on a road, in a country that requires all vehicles to keep to the left side of the road. 
       1. Segmenting Operation of First Embodiment 
       [0101]    In step S 6  of  FIG. 7 , the ECU  22  segments a captured image  134  as a grayscale image into three sub-regions, i.e., a central region corresponding to a central range including the direction of travel of the vehicle  12 , a left region corresponding to a left range to the left of the central range, and a right region corresponding to a right range to the right of the central range. The ranges are included in an image range captured in front of the vehicle  12  by the infrared camera  16 R (see  FIG. 13A , etc.). A specific process of segmenting the captured image  134  into three sub-regions will be described below with reference to  FIG. 12 . In  FIG. 12 , it is assumed that a biological target, which exists in front of the vehicle  12 , is an animal  160  (see  FIG. 13A , etc.). 
         [0102]    The captured image  134  is segmented into a central region  154 C corresponding to a central range including the direction of travel of the vehicle  12 , a left region  154 L corresponding to a left range to the left of the central range, and a right region  154 R corresponding to a right range to the right of the central range. The ranges are included in a captured image range in front of the vehicle  12 . The captured image  134  is segmented into the central region  154 C, the left region  154 L, and the right region  154 R by a left boundary line  151 L, which is disposed to the left of the central region  154 C, and a right boundary line  151 R, which is disposed to the right of the central region  154 C. Segmentation of the captured image  134  shown in  FIG. 12  represents a segmentation that is based on initial settings. According to the initial settings on which the segmentation is based, the captured image  134  is segmented into three equal regions along the lateral or horizontal direction. 
         [0103]    The left boundary line  151 L and the right boundary line  151 R are used in a process of generating an icon image  144 . The left boundary line  151 L and the right boundary line  151 R are not displayed in the actual captured image  134  on the general-purpose monitor  26 . Data for generating the captured image  134  represent brightness data of the pixels that make up the captured image  134 . Based on which region each of the pixels of the pixel group belongs to, i.e., the left region  154 L, the central region  154 C, or the right region  154 R, it is judged whether a group of pixels making up a monitored target image belongs to the left region  154 L, the central region  154 C, or the right region  154 R. 
         [0104]    A relationship between the left boundary line  151 L and the right boundary line  151 R, and a lateral field of view of the infrared camera  16 R in  FIG. 12  will be described below with reference to  FIGS. 13A and 13B . Left and right ends of the captured image  134  are determined by a left demarcating line  161 L and a right demarcating line  161 R, which serve to demarcate the lateral field of view of the infrared camera  16 R within a lateral viewing angle α of the infrared camera  16 R. In other words, only an object that exists within the lateral field of view between the left demarcating line  161 L and the right demarcating line  161 R is imaged by the infrared camera  16 R and is converted into an image area in the captured image  134 . Objects that exist outside of the lateral field of view between the left demarcating line  161 L and the right demarcating line  161 R are excluded from the captured image  134 . 
         [0105]    A central viewing angle β is defined within the lateral viewing angle α and left and right ends thereof are demarcated by an inner left demarcating line  166 L and an inner right demarcating line  166 R, respectively. The inner left demarcating line  166 L and the inner right demarcating line  166 R specify the left boundary line  151 L and the right boundary line  151 R, respectively, in the captured image  134 . In other words, an image area representing an object within the central viewing angle β is displayed in the central region  154 C of the captured image  134 . 
         [0106]      FIG. 12  shows in a lower portion thereof three icon images  144 , which are arranged laterally or horizontally. The icon images  144  include respective road icons  145  and respective animal icons  157 , which are located in a left position, a central position, and a right position, respectively, successively from the left to the right. In each of the icon images  144 , the road icon  145  and the animal icon  157  are located in respective upper and lower positions. The road icon  145  is made up of three lines including left and right lines and a central line. The width of the gap between the left and right lines becomes progressively smaller toward the upper end, suggesting a remote position, and thus representing a scene in front of the vehicle  12  as observed from the perspective of the driver&#39;s seat in the vehicle  12 . 
         [0107]    In the first icon image  144  from the left, the animal icon  157  is displayed in a left-hand position to the left of the left line of the road icon  145 , which is displayed obliquely upward to the right. In the second icon image  144  from the left, the animal icon  157  is displayed in a central position on an upward extension of the central line of the road icon  145 . In the third icon image  144  from the left, the animal icon  157  is displayed in a right-hand position to the right of the right line of the road icon  145 , which is displayed obliquely upward to the left. 
         [0108]    The three icon images  144  shown in the lower portion of  FIG. 12  are displayed on the MID  28  when an animal image area  149  (target image area) in the captured image  134  belongs to the left region  154 L, the central region  154 C, and the right region  154 R, respectively. 
         [0109]    If there are a plurality of targets existing in front of the vehicle  12 , then a plurality of animal icons  157  corresponding to the targets are displayed in the icon images  144  at positions of the targets, which are spaced along the transverse direction of the vehicle  12 . If plural biological image areas belong to one region, then the MID  28  may display only one biological icon at a position corresponding to that region. 
         [0110]    As shown in the upper portion of  FIG. 12 , the captured image  134  is segmented into the left region  154 L, the central region  154 C, and the right region  154 R. The relationship between the distance from the vehicle  12  to the animal  160 , as a biological target, and the region to which the animal image area  149  corresponding to the animal  160  belongs in the captured image  134  will be described below with reference to  FIGS. 13A and 13B . 
         [0111]    As shown in  FIGS. 13A and 13B , it is assumed that the animal  160  actually exists leftward and outwardly of a left-hand side edge of a road  131 . When the animal  160  is sufficiently far from the vehicle  12 , as shown in  FIG. 13A , the animal  160  is positioned inside the central viewing angle β. As the vehicle  12  moves closer to the animal  160  while the animal  160  remains unchanged in position, as shown in  FIG. 13B , the animal  160  becomes positioned outside of the central viewing angle β. 
         [0112]    As the biological target becomes positioned farther from the vehicle  12 , a corresponding biological icon tends to be displayed at a central position on the MID  28 . Since a farther-distanced biological target, which exists within an attention calling distance, becomes more uncertain in position when the vehicle  12  actually moves closer toward the biological target, the MID  28  displays a corresponding biological icon at a central position, thereby calling attention from the driver. 
         [0113]    A biological target, which is positioned farther from the vehicle  12 , results in a corresponding biological image area having smaller dimensions in the captured image  134 . If the size of the biological image area in the captured image  134  is smaller than a predetermined threshold value, then the biological image area is not extracted as a biological target. When a biological target is positioned farther from the vehicle  12  beyond a predetermined distance, even if the biological target exists within the central viewing angle β, the MID  28  does not display a corresponding biological icon in the icon image  144 . The distance from the vehicle  12  up to a biological target is calculated based on a parallax effect developed by the infrared cameras  16 R,  16 L with respect to the biological target. 
         [0114]    When the driver observes the MID  28  and sees an animal icon  157  displayed in the icon image  144  on the MID  28 , the driver knows that an animal  160  exists in front of the vehicle  12 . With respect to the position of the animal  160  along the transverse direction of the vehicle  12 , from the lateral position of the animal icon  157  with respect to the road icon  145  on the MID  28 , the driver can judge whether the animal  160  exists in a central, left, or right area in front of the vehicle  12 , without the need to move the driver&#39;s eyes from the MID  28  to the general-purpose monitor  26 . 
         [0115]    A biological target is more likely to collide with the vehicle  12  when the biological target resides within a central range including the direction of travel of the vehicle  12  than when the biological target is in a left range or a right range on one side of the central range. Therefore, when a biological icon is in a central position in the icon image  144 , i.e., the second icon image  144  from the left in the lower portion of  FIG. 12 , the driver is advised to pay more attention than when the biological icon is in a left position or a right position in the icon image, i.e., the first or third icon image  144  from the left in the lower portion of  FIG. 12 . 
         [0116]    Segmentation according to the first embodiment represents a segmentation of the captured image  134  into three equal regions based on initial settings. However, various improvements may be made to the way in which segmentation is performed. 
       2. First Improvement 
       [0117]      FIG. 14  is a flowchart of a processing sequence for adjusting segmentation based on the lateral position of an animal icon  157  in an icon image  144  depending on a turn made by the vehicle  12 . Segmentation based on initial settings need not necessarily be a segmentation of the captured image  134  into three equal regions. Rather, segmentation based on the initial settings may be defined by segmentation of the captured image  134  into a left region  154 L, a right region  154 R, and a central region  154 C, which is wider or narrower than the left region  154 L and the right region  154 R. 
         [0118]    In step S 11 , the ECU  22  segments a captured image  134 , which is to be displayed on the general-purpose monitor  26 , based on initial settings. More specifically, the ECU  22  divides the lateral viewing angle α into three angle segments, i.e., a left angle segment, a central angle segment, and a right angle segment, and with a left boundary line  151 L and a right boundary line  151 R, segments the captured image  134  into three laterally equal regions, i.e., a left region  154 L, a central region  154 C, and a right region  154 R. 
         [0119]    In step S 12 , the ECU  22  checks if the vehicle  12  is making a right turn. If the vehicle  12  is making a right turn, then control proceeds to step S 13 . If the vehicle  12  is not making a right turn, then step S 13  is skipped and control proceeds to step S 14 . Based on an output signal from the yaw rate sensor  20 , the ECU  22  can determine whether the vehicle  12  is traveling straight forward, is making a right turn, or is making a left turn. 
         [0120]    In step S 13 , the ECU  22  shifts the left boundary line  151 L a predetermined distance to the left in the captured image  134 . The reasons why the left boundary line  151 L or the right boundary line  151 R is shifted depending on the direction in which the vehicle  12  is turned will be described below with reference to  FIGS. 15A through 15C . 
         [0121]    In  FIGS. 15A through 15C , it is assumed that an animal  160  exists on a road  131  near a left side edge thereof and within a right curve of the road  131 .  FIGS. 15A through 15C  show a captured image  134  of the animal  160 , which is displayed on the general-purpose monitor  26 , and an icon image  144  of the animal  160 , which is displayed on the MID  28 . 
         [0122]    In  FIG. 15A , a road image area  140  is shown in which the vehicle  12  is traveling on a straight road section prior to a right curve (see  FIG. 12 ). While the vehicle  12  is traveling straight, the captured image  134  is segmented based on initial settings. The animal  160  exists near the central line in the lateral viewing angle α and within the central viewing angle β. As a result, an animal image area  149  is displayed in the central region  154 C of the captured image  134 , and the animal icon  157  is disposed at a central position in the icon image  144 . 
         [0123]      FIGS. 15B and 15C  show captured images  134  and icon images  144 , which are displayed while the vehicle  12  is making a right turn by moving into a right curve of the road image area  140  where the animal  160  exists.  FIG. 15B  shows the captured image  134  and the icon image  144 , which are displayed, and in which the segmentation of the captured image  134  remains unchanged corresponding to the segmentation based on the initial settings.  FIG. 15C  shows the captured image  134  and the icon image  144 , which are displayed, and in which the segmentation of the captured image  134  is changed from the segmentation based on the initial settings (see step S 11 ). 
         [0124]    The horizontal distance between the vehicle  12  and a target exiting near an edge of the road  131  tends to become greater while the vehicle  12  is traveling on a curved road than while the vehicle  12  is traveling on a straight road. While the vehicle  12  is making a right turn, as shown in  FIG. 15B , if segmentation of the captured image  134  remains the same as the segmentation based on the initial settings for traveling straight as shown in  FIG. 15A , then even though an actual animal  160  exists on the road  131 , an animal image area  149  corresponding to the animal  160  is positioned leftwardly of the inner left demarcating line  166 L. Therefore, the animal image area  149 , which corresponds to the animal  160 , belongs to the left region  154 L of the captured image  134 , and the animal  160  is represented by an animal icon  157  in a left-hand position, i.e., as a target outside of the road  131 , in the icon image  144 . Stated otherwise, the position of the animal icon  157  differs from the actual position of the animal  160  with respect to the road  131 . 
         [0125]    While the vehicle  12  is making a right turn, the ECU  22  carries out the process of step S 13 , so as to shift the inner left demarcating line  166 L to the left outwardly along the direction of the turn by an angle q, as shown in  FIG. 15C , thereby bringing the animal  160  inwardly of the inner left demarcating line  166 L along the lateral direction of the vehicle  12 . As a result, in the captured image  134 , the left boundary line  151 L is shifted to the left by a dimension Q. Although the animal image area  149  remains in the same position in the captured image  134 , the animal  160  is displayed in the icon image  144  by the animal icon  157  as a target on the road  131 . Consequently, while the vehicle  12  is making a turn, the driver can properly recognize the position of the animal  160  with respect to the road  131  along the transverse direction of the vehicle  12 . 
         [0126]    In step S 14  of  FIG. 14 , the ECU  22  checks if the vehicle  12  is making a left turn. If the vehicle  12  is making a left turn, then control proceeds to step S 15 . If the vehicle  12  is not making a left turn, then the process of step S 6 , i.e., the turn-dependent segmentation process, is brought to an end. While the vehicle  12  is traveling straight, therefore, the captured image  134  is segmented into the left region  154 L, the central region  154 C, and the right region  154 R, according to the segmentation based on the initial settings. In step S 15 , the ECU  22  shifts the right boundary line  151 R a predetermined distance to the right in the captured image  134 . 
         [0127]    The process of shifting the left boundary line  151 L to the left while the vehicle  12  makes a right turn has been described above with reference to  FIGS. 15A through 15C . The same description applies to the process of step S 15 , in which the right boundary line  151 R is shifted to the right while the vehicle  12  makes a left turn. 
       3. Second Improvement 
       [0128]      FIG. 16  is a flowchart of a processing sequence for adjusting segmentation based on the lateral position of a human icon  136  in an icon image  144  depending on the vehicle speed V. 
         [0129]    In step S 21 , based on the initial settings, the ECU  22  segments a captured image  134  to be displayed on the general-purpose monitor  26 . The process of step S 21  is the same as in the first improvement (see step S 11  of  FIG. 14 ) described above, and thus will not be described in detail below. 
         [0130]    In step S 22 , the ECU  22  checks if the vehicle speed V is equal to or greater than a threshold value. If the vehicle speed V is equal to or greater than the threshold value, then control proceeds to step S 23 . If the vehicle speed V is not equal to or greater than the threshold value, then the vehicle-speed-dependent segmentation process is brought to an end. In step S 23 , the ECU  22  shifts the left boundary line  151 L and the right boundary line  151 R laterally outward. 
         [0131]    Specific modes of displaying icon images  144  will be described below with reference to  FIGS. 17A and 17B . The threshold value shown in  FIG. 16  (see step S 22 ) is set to 60 [m/h], for example.  FIG. 17A  shows a vehicle speed V of 30 [m/h], which is an example lower than the threshold value (when the vehicle speed V is low), and  FIG. 17B  shows a vehicle speed V of 70 [m/h], which is an example higher than the threshold value (when the vehicle speed V is high). 
         [0132]    In  FIGS. 17A and 17B , it is assumed that a person  110  is positioned in the vicinity of the road  131  and to the left and to the right of the road  131  in front of the vehicle  12 .  FIG. 17A  shows a central viewing angle β 1 , which represents a value of the central viewing angle β for carrying out segmentation based on the initial settings. The central viewing angle β 1  is defined between an inner left demarcating line  166 L and an inner right demarcating line  166 R, which serve as straight lines that divide the lateral viewing angle α into three equal angles. Therefore, β 1 =α/3.  FIG. 17B  shows a central viewing angle β 2 , which represents a value of the central viewing angle β that is wider than the central viewing angle β 1  for carrying out segmentation based on the initial settings. Therefore, β 2 &gt;β 1 . 
         [0133]    When the vehicle speed V is low ( FIG. 17A ), a left boundary line  151 L and a right boundary line  151 R are set to positions corresponding to the central viewing angle β 1  for carrying out segmentation based on the initial settings. Depending on the central viewing angle β 1 , the dimension between the left boundary line  151 L and the right boundary line  151 R is represented by “a” in the captured image  134  on the general-purpose monitor  26 . At this time, since a human image area  133  (target image area) in the captured image  134  belongs to the left region  154 L, a human icon  136  is displayed at a left position in the icon image  144 . 
         [0134]    When the vehicle speed V is high ( FIG. 17B ), depending on the central viewing angle β 2 , the dimension between the left boundary line  151 L and the right boundary line  151 R is represented by “b” (b&gt;a) in the captured image  134  on the general-purpose monitor  26 . As a result, since a human image area  133  in the captured image  134  belongs to the central region  154 C, a human icon  136  is displayed at a central position in the icon image  144 . 
         [0135]    While the vehicle  12  is traveling at high speed, the time required for the vehicle  12  to approach a target in front of the vehicle  12  is shorter than while the vehicle  12  is traveling at low speed, and thus, the driver needs to pay more attention to the target. While the vehicle  12  is traveling at high speed, in step S 23 , the left boundary line  151 L between the central region  154 C and the left region  154 L, and the right boundary line  151 R between the central region  154 C and the right region  154 R are displaced toward the left region  154 L and the right region  154 R, respectively. Consequently, a biological image area such as the human image area  133 , which normally is displayed as belonging to the left region  154 L or the right region  154 R on the MID  28  while the vehicle  12  is traveling at low speed, is displayed as belonging to the central region  154 C on the MID  28  while the vehicle  12  is traveling at high speed. Therefore, while the vehicle  12  is traveling at high speed, the distance from the vehicle  12  to the biological target at the time that attention starts to be called from the driver is increased, so as to prevent a delay in calling the attention of the driver. 
         [0136]    In the vehicle-speed-depending segmentation process shown in  FIGS. 17A through 17B , the dimension between the left boundary line  151 L and the right boundary line  151 R changes between the two dimensions “a” and “b”. However, the dimension between the left boundary line  151 L and the right boundary line  151 R may change between three or more dimensions depending on the vehicle speed V. Furthermore, the dimension between the left boundary line  151 L and the right boundary line  151 R may be changed continuously depending on the vehicle speed V. 
       4. Supplementary Remarks 
       [0137]    The segmentation process, which is improved in the foregoing manner, allows the driver to pay attention according to an appropriate process, which depends on the manner in which the vehicle  12  is presently being driven. The above modifications may be applied to the first embodiment or to a second embodiment, which will be described in detail below. 
       C. Second Embodiment 
       [0138]    A vehicle periphery monitoring apparatus  210  according to a second embodiment of the present invention will be described below. 
       [1. Arrangement] 
       [0139]      FIG. 18  is a block diagram showing the arrangement of the vehicle periphery monitoring apparatus  210  according to the second embodiment of the present invention. The vehicle periphery monitoring apparatus  210  includes infrared cameras  16 L,  16 R, a vehicle speed sensor  18 , a yaw rate sensor  20 , a speaker  24 , a general-purpose monitor  26 , an MID  28  (refer to the vehicle periphery monitoring apparatus  10  shown in  FIG. 1 ), a brake sensor  19 , and an image processing unit  214 . The brake sensor  19  detects a depth Br to which the brake pedal of the vehicle  12  is depressed by the driver (hereinafter referred to as a “brake pedal depression depth Br”) and supplies the detected brake pedal depression depth Br to the image processing unit  214 . 
         [0140]    The image processing unit  214 , which controls the vehicle periphery monitoring apparatus  210 , includes an A/D conversion circuit, not shown, for converting supplied analog signals into digital signals, a CPU (Central Processing Unit)  214   c  for performing various processing operations, a memory  214   m  for storing various data used in an image processing routine, and an output circuit, not shown, for supplying drive signals to the speaker  24  as well as display signals to the general-purpose monitor  26  and the MID  28 . 
         [0141]    The CPU  214   c  functions as a target detector  240 , a position calculator  242 , which includes a first position calculator  244 , a second position calculator  246 , and an actual position calculator  248 , an attention degree evaluator  250 , which includes a sole evaluator  252  and a comparative evaluator  254 , and a display mark determiner  256 . 
         [0142]      FIG. 19A  is a front elevational view of the general-purpose monitor  26 , and  FIG. 19B  is a front elevational view of the MID  28 . 
         [0143]    The general-purpose monitor  26  shown in  FIG. 19A  has a horizontally elongate rectangular first display region  260  arranged substantially on the front surface thereof. In  FIG. 19A , the general-purpose monitor  26  displays a first image  262 , which is based on a captured image signal supplied from the infrared camera  16 L, in the first display region  260 . 
         [0144]    The MID  28  shown in  FIG. 19B  has a horizontally elongate rectangular second display region  264  arranged substantially on the front surface thereof. In  FIG. 19B , the MID  28  displays a second image  266 , which represents a predetermined feature area extracted and modified from the first image  262 , in the second display region  264 . In  FIG. 19B , a road icon  268  is displayed as a specific example in a lower portion of the second display region  264 . The road icon  268  is made up of three lines, i.e., lines  267 L,  267 C,  267 R, which are arranged successively from the left. 
         [0145]    The vehicle periphery monitoring apparatus  210  is incorporated in a vehicle  12 , in the same manner as the vehicle periphery monitoring apparatus  10  according to the first embodiment (see  FIGS. 2 and 3 ). Therefore, specific descriptions of the manner in which the vehicle periphery monitoring apparatus  210  is incorporated in the vehicle  12  will be omitted below. The vehicle periphery monitoring apparatus  210  according to the second embodiment basically is constructed as described above. 
       [2. Operations of Vehicle Periphery Monitoring Apparatus  210 ] 
       [0146]    Operations of the vehicle periphery monitoring apparatus  210  will be described below with reference to the flowchart shown in  FIG. 20  as well as other figures. 
         [0147]    In step S 31 , the image processing unit  214  acquires captured image signals at the present time from the infrared cameras  16 L,  16 R, which capture images of the periphery of the travelling vehicle  12 . If the infrared cameras  16 L,  16 R capture images at intervals of about 33 ms, for example, then either one of the infrared cameras  16 R or  16 L continuously or intermittently produces a captured image signal having 30 frames per second. 
         [0148]    In step S 32 , the image processing unit  214  supplies the captured image signal from one of the infrared cameras  16 L,  16 R, e.g., the infrared camera  16 L, to the general-purpose monitor  26 . The general-purpose monitor  26  displays a first image  270  ( FIG. 21A ) or  272  ( FIG. 21B ), which is captured at the present time, in the first display region  260  (see  FIG. 19A ). The general-purpose monitor  26  is capable of displaying various images apart from the first image  270  or  272 , depending on settings established by a non-illustrated operating unit. If the general-purpose monitor  26  is currently displaying another image or video image, then the present step is omitted. 
         [0149]    The first image  270  in  FIG. 21A  shows a human area H 1  (actually, a single human) as a target image area, which exists in a road surface region Rd (actually, a road surface). The first image  272  in  FIG. 21B  shows the human area H 1 , which exists in the road surface region Rd, and another human area H 2  (actually, another single human) as a target image area, which exists at an edge (actually, a road shoulder) of the road surface region Rd. 
         [0150]    In step S 33 , the target detector  240  detects a monitored target from an image region represented by the captured image signal. Examples of the monitored target include various animals (specifically, mammals such as deer, horses, sheep, dogs, cats, etc., birds, etc.) and artificial structures (specifically, power poles, guardrails, walls, etc.). The target detector  240  may make use of any appropriate one of various known detecting algorithms, which is suitable for the type of target that is monitored. 
         [0151]    In step S 34 , the first position calculator  244  calculates the position or an existing range (hereinafter referred to as a “first position”) of each of the monitored targets in the first display region  260 . If the general-purpose monitor  26  possesses high display resolution, then the first position calculator  244  is capable of identifying the position of the monitored targets with high accuracy. 
         [0152]    In step S 35 , the second position calculator  246  calculates the position of each of the monitored targets (hereinafter referred to as a “second position”) in the second display region  264 . The associated relationship between the first position in the first display region  260  and the second position in the second display region  264  will be described below with reference to  FIG. 22 . 
         [0153]    As shown in  FIG. 22 , the first display region  260  of the general-purpose monitor  26  is divided into three equal regions, i.e., a left region  274 , a central region  276 , and a right region  278 , which are arranged successively from the left. The second display region  264  of the MID  28  includes three positions defined therein, i.e., a left position  284 , a central position  286 , and a right position  288 , which are arranged successively from the left. The left region  274  is associated with the left position  284 , the central region  276  is associated with the central position  286 , and the right region  278  is associated with the right position  288 . 
         [0154]    Division of the first display region  260  is not limited to the example shown in  FIG. 22 , and the first display region  260  may be divided in other ways. For example, the first display region  260  may be divided into two regions or four or more regions. The central region  276  may be greater (or smaller) in size than the left region  274  and the right region  278 . The first display region  260  may be divided vertically rather than horizontally. Furthermore, the first display region  260  may be divided along road lanes, i.e., into regions that are shaped in the form of an inverted chevron. 
         [0155]    In step S 36 , the target detector  240  judges whether or not a plurality of monitored targets are detected from the result of step S 33 . If no monitored target or if only one monitored target is detected, then in step S 38 , the image processing unit  214  supplies the MID  28  with a display signal representing the second image  266  (see  FIG. 19B ), or a display signal representing a second image  289  (see  FIG. 23 ). The MID  28  displays the second image  289  at the present time in the second display region  264 . 
         [0156]    Prior to displaying the second image  289  ( FIG. 23 ), the display mark determiner  256  determines the form (e.g., shape, color, etc.) of a mark to be displayed on the MID  28 . In the first image  270  shown in  FIG. 21A , since the human area H 1  is detected in the central region  276  (see  FIG. 22 ) of the first display region  260 , the display mark determiner  256  determines that a human icon in an ordinary display color (e.g., white) should be placed at the central position  286  (see  FIG. 22 ). 
         [0157]    As a result, as shown in  FIG. 23 , a white human icon  290  is displayed substantially centrally in the second display region  264 . Inasmuch as the human icon  290 , which is shaped like the monitored target, is displayed as a mark on the MID  28 , the driver can recognize the type of monitored target at a glance. If the type of monitored target is an animal, then an animal icon may be displayed as a mark on the MID  28 . Therefore, the second image  289  corresponds to an image in which information (type, existence or non-existence, number) is visualized as to whether a monitored target exists or not. 
         [0158]    When marks are displayed respectively in positions (the left position  284 , the central position  286 , and the right position  288 ) that match the layout of the three sub-regions (the left region  274 , the central region  276 , and the right region  278 ), the driver can instinctively recognize whether or not a monitored target exists, as well as the position of a monitored target, if any. 
         [0159]    In step S 39 , the image processing unit  214  determines whether or not there is a possibility of collision of the vehicle  12  with a monitored target. If the image processing unit  214  judges that there is no possibility of collision of the vehicle  12  with a monitored target, then control returns to step S 31 , and steps S 31  through S 38  are repeated. 
         [0160]    If the image processing unit  214  judges that there is a possibility of collision of the vehicle  12  with a monitored target, then the vehicle periphery monitoring apparatus  210  produces a warning sound via the speaker  24 , for example, thereby giving the driver information concerning the possibility of a collision in step S 40 . Accordingly, the driver is prompted to control the vehicle  12  to avoid the collision. 
       [3. Description of Step S 37 ] 
       [0161]    If two or more monitored targets are detected in step S 36  in  FIG. 20 , then control proceeds to step S 37 . As shown in  FIG. 21B , it is assumed that one monitored target exists in each of the central region  276  and in the right region  278  (see  FIG. 22 ), for example. 
         [0162]    According to the present embodiment, the attention degree evaluator  250  evaluates the possibility of collision of a monitored target with the vehicle  12  (hereinafter referred to as a “degree of risk”). A process of evaluating a degree of risk, which is performed in step S 37 , will be described in detail below with reference to the flowchart shown in  FIG. 24 . 
         [0163]    In step S 51 , the attention degree evaluator  250  designates a monitored target which is yet to be evaluated. The sole evaluator  252  evaluates a degree of risk at the present time with respect to the designated monitored target in view of various states, i.e., by implementing steps S 52  through S 57 , to be described below. 
         [0164]    In step S 52 , the sole evaluator  252  evaluates a degree of risk of collision of a monitored target with the vehicle  12  from the positional relationship between the monitored target and the vehicle  12 . Prior to evaluating the degree of risk, the actual position calculator  248  calculates the actual position of the monitored target, e.g., a human body corresponding to the human area H 1 , and the actual distance between the monitored target and the vehicle  12 , from a pair of captured image signals from the infrared cameras  16 R,  16 L, according to a known process such as triangulation. If the distance between the monitored target and the vehicle  12  is small, then the sole evaluator  252  judges that there is a high possibility of collision of the vehicle  12  with the monitored object. On the other hand, if the distance between the monitored target and the vehicle  12  is large, then the sole evaluator  252  judges that there is a low possibility of collision of the vehicle  12  with the monitored object. 
         [0165]    In step S 53 , the sole evaluator  252  evaluates a degree of risk of collision of the vehicle  12  with a monitored target from the direction of movement of the monitored target. 
         [0166]      FIGS. 25A through 25C  are views illustrating a process of evaluating a degree of risk from a direction along which the monitored target moves. It is assumed that a first pedestrian existing on the road surface traverses the road, whereas a second pedestrian walks along a road shoulder. The human area H 1  shown in  FIG. 25A  (first image  272 ) moves over time along the direction of the arrow MV 1 , or stated otherwise, moves to the position shown in  FIG. 25B  (first image  272   a ), and thereafter, the human area H 1  moves to the position shown in  FIG. 25C  (first image  272   b ). The human area H 2  shown in  FIG. 25A  moves over time along the direction of the arrow MV 2 , or stated otherwise, moves to the position shown in  FIG. 25B , and thereafter, moves to the position shown in  FIG. 25C . The arrow MV 1  represents a motion vector (distance moved per unit time) of the first pedestrian, whereas the arrow MV 2  represents a motion vector (distance moved per unit time) of the second pedestrian. 
         [0167]    The sole evaluator  252  evaluates a degree of risk of collision of the vehicle  12  with the monitored targets depending on the motion vectors, or more specifically, depending on directions of the motion vectors. For example, since the motion vector MV 1  of the human area H 1  lies substantially parallel to the horizontal direction of the first image  272 , the sole evaluator  252  presumes that the human area H 1  represents a pedestrian walking across the road, and judges that the vehicle  12  has a high degree of risk of colliding with the monitored target. On the other hand, since the motion vector MV 2  of the human area H 2  is inclined a certain angle or greater with respect to the horizontal direction of the first image  272 , the sole evaluator  252  presumes that the human area H 2  does not represent a pedestrian walking across the road, and judges that the vehicle  12  has a low degree of risk of colliding with the monitored target. 
         [0168]    In step S 54 , the sole evaluator  252  evaluates a degree of risk of collision of the vehicle  12  with a monitored target depending on a predicted route followed by the vehicle  12 . 
         [0169]    As shown in  FIGS. 26A and 26B , imaginary lines P 1 , P 2 , as indicated by the dot-and-dash lines, are drawn on the first image  272  along the direction of travel of the vehicle  12 . The direction of travel is indicated by the arrows. The imaginary lines P 1 , P 2  represent a predicted route to be followed by the vehicle  12 . 
         [0170]    In  FIG. 26A , the distance that the human area H 1  is spaced from the predicted route P 1  is smaller than the distance that the human area H 2  is spaced from the predicted route P 1 . Therefore, the sole evaluator  252  predicts that the vehicle  12  is likely to collide with the first pedestrian (human area H 1 ) if the vehicle  12  is driven continuously in the same manner, and judges that the vehicle  12  has a high degree of risk of colliding with the monitored target. On the other hand, the sole evaluator  252  predicts that the vehicle  12  is not likely to collide with the second pedestrian (human area H 2 ) if the vehicle  12  is driven continuously in the same manner, and judges that the vehicle  12  has a low degree of risk of colliding with the monitored target. 
         [0171]    In  FIG. 26B , the distance that the human area H 1  is spaced from the predicted route P 2  is greater than the distance that the human area H 2  is spaced from the predicted route P 2 . Therefore, assuming that the vehicle  12  is driven continuously in the same way, the sole evaluator  252  predicts that the vehicle  12  is likely to collide with the second pedestrian (human area H 2 ), and judges that the vehicle  12  has a high degree of risk of colliding with the monitored target. On the other hand, assuming that the vehicle  12  is driven continuously in the same way, the sole evaluator  252  predicts that the vehicle  12  is not likely to collide with the first pedestrian (human area H 1 ), and judges that the vehicle  12  has a low degree of risk of colliding with the monitored target. 
         [0172]    In step S 55 , the sole evaluator  252  evaluates a degree of risk of collision of the vehicle  12  with a monitored target from the ease with which the driver is able to locate the monitored target. More specifically, a state in which the driver finds it difficult to locate the monitored target is presupposed, and the sole evaluator  252  evaluates the presupposed state as having a high degree of risk, regardless of whether or not the driver has actually located the monitored target. For example, the presupposed state may represent a detected area having a small size, a small movement distance (motion vector), a detected area having a shape that differs from a normal shape, etc. Specific examples of detected areas having a normal shape include a walking pedestrian, a running pedestrian, a standing pedestrian, etc., whereas specific examples of detected areas having an abnormal shape include a squatting pedestrian, a pedestrian who is lying down, etc. 
         [0173]    The driver also finds it difficult to locate a monitored target if a difference in color between the color of the monitored target and the background color is small, for example, when a pedestrian is wearing neutral and dark clothes at night. Such a monitored target can be distinguished based on a difference between the brightness of the monitored target and the background brightness, in a grayscale image acquired by the infrared cameras  16 L,  16 R. The monitored target can also be distinguished based on a difference between the color of the monitored target and the background color in a color space such as CIERGB, CIELAB, or the like, in a color image acquired by a color camera. 
         [0174]    In step S 56 , from the ability of the monitored target to recognize the existence of the vehicle  12 , the sole evaluator  252  evaluates a degree of risk of collision of the vehicle  12  with a monitored target. More specifically, a state in which the monitored target is incapable of recognizing the existence of the vehicle  12  is presupposed, and the sole evaluator  252  evaluates the presupposed state as having a high degree of risk, regardless of whether or not the monitored target actually has recognized the existence of the vehicle  12 . For example, the sole evaluator  252  can judge whether or not the vehicle  12  lies within the field of vision of the monitored target, by detecting the attitude of the monitored target (e.g., a facial direction if the monitored target is a human). The sole evaluator  252  may evaluate a face that is directed away from the vehicle  12 , a face that is directed sideways, and a face that is directed toward the vehicle  12  as possessing progressively lower degrees of risk. 
         [0175]    The direction of the face can be detected with high accuracy based on the brightness of a binary image of the head, i.e., the ratio of on-pixels of the binary image. If a human turns his or her face toward the vehicle  12 , the area of bare skin (on-pixels) of the head becomes greater, whereas if a human turns his or her back toward the vehicle  12 , the area of hair (off-pixels) of the head becomes greater. The sole evaluator  252  may also presume intermediate states (facing sideways or facing obliquely), other than the states of facing toward the vehicle  12  and facing away from the vehicle  12 . 
         [0176]    The sole evaluator  252  may further presume the situation judging ability and/or behavior predictability of a monitored target, and reflect the presumed situation judging ability and/or behavior predictability in evaluating a degree of risk. For example, based on the shape or behavior of the detected area of the monitored target, the sole evaluator  252  may judge whether a monitored target, which is judged as being a human, is an elderly person or a child, and evaluate the judged and monitored target as having a high degree of risk. 
         [0177]    In step S 57 , the sole evaluator  252  makes a comprehensive evaluation of a degree of risk of the monitored target that was designated in step S 51 . The degree of risk may be represented in any data format, such as a numerical value or a level. The levels of importance (weighting) of evaluation values, which are calculated in steps S 52  through S 56 , may be changed as desired. For example, a degree of risk basically is evaluated based on the positional relationship between a monitored target and the vehicle  12  (see step S 52 ). Further, if plural monitored targets having a high degree of risk are present, then other evaluation values (see steps S 53  through S 56 ) may also be taken into account for carrying out evaluation thereof. 
         [0178]    In step S 53 , the accuracy in evaluating the degree of risk is increased by also taking into account a predicted motion of a monitored target. In step S 54 , the accuracy in evaluating the degree of risk is increased by also taking into account a predicted route followed by the vehicle  12 . In step S 55 , the accuracy in evaluating the degree of risk is increased by also taking into account an evaluation from the viewpoint of the driver. In step S 56 , the accuracy in evaluating the degree of risk is increased by also taking into account an evaluation from the viewpoint of the monitored target. The first image  272  or other items of input information, e.g., the vehicle speed V, the brake pedal depression depth Br, the yaw rate Yr, and distance information which is acquired from a GPS (Global Positioning System) or a distance measuring means, may be used in evaluating the degrees of risk in steps S 53  through S 56 . 
         [0179]    In step S 58 , the attention degree evaluator  250  judges whether or not all of the processes of evaluating each monitored target have been completed. If the attention degree evaluator  250  judges that all of the evaluating processes have not been completed, then control returns to step S 51 , and steps S 51  through S 57  are repeated until all of the evaluating processes have been completed. If the attention degree evaluator  250  judges that all of the evaluating processes have been completed, then control proceeds to step S 59 . 
         [0180]    In step S 59 , the comparative evaluator  254  selects at least one monitored target as having a high degree of risk from among a plurality of monitored targets. The comparative evaluator  254  may select only one monitored target, or two or more monitored targets, as having a high degree of risk. It is assumed that the human area H 1  is selected from two monitored targets (human areas H 1 , H 2 ). 
         [0181]    In this manner, step S 37  comes to an end. In step S 38 , the MID  28  displays a second image  291  at the present time in the second display region  264  (see  FIG. 19B ). 
         [0182]    Prior to displaying the second image  291 , the display mark determiner  256  determines the form of the mark to be displayed on the MID  28 . In the first image  272  shown in  FIG. 21B , since the human area H 1  is detected in the central region  276  (see  FIG. 22 ) of the first display region  260 , the display mark determiner  256  determines that a human icon should be placed at the central position  286  (see  FIG. 22 ). Since the human area H 2  is detected in the right region  278  (see  FIG. 22 ) of the first display region  260 , the display mark determiner  256  determines that a human icon should be placed at the right position  288  (see  FIG. 22 ). Further, since the comparative evaluator  254  has evaluated that the degree of risk of the human area H 1  is higher, the display mark determiner  256  displays the human icon, which is placed at the central position  286 , in a more noticeable display color (e.g., red), and displays the human icon, which is placed at the right position  288 , in an ordinary display color (e.g., white). 
         [0183]    As a result, as shown in  FIG. 27 , the second display region  264  displays a red human icon  292  in a substantially central region thereof, and also a white human icon  294  in a right-hand region thereof. When the driver sees the MID  28 , the driver&#39;s eyes turn toward the red human icon  292 , which is visually highlighted. Based on the relative positional relationship between the human icon  292  and the first display region  260 , increased alertness in the driver is aroused and directed toward the central region of the first image  272 , i.e., the area in front of the vehicle  12 . In other words, the existence of a monitored target, the attention level of which is relatively high from among a plurality of monitored targets, is indicated prominently to the driver. 
         [0184]    The human icons  292 ,  294  may be displayed in different display modes, for example, by displaying the human icon  292  in a way less noticeable than ordinary, rather than displaying the human icon  294  in a way more noticeable than ordinary, or by displaying the human icons  292 ,  294  in combined ways less and more noticeable than ordinary. The different display modes for displaying the human icons  292 ,  294  may include, other than different colors, any means such as different shapes (e.g., sizes), or different visual effects (e.g., blinking or fluctuating), insofar as such modes of display can impart relative visibility differences to a plurality of marks. 
       [4. Advantages] 
       [0185]    According to the second embodiment, when monitored targets (human areas H 1 , H 2 ) are detected from two or more sub-regions (e.g., the central region  276  and the right region  278 ), the MID  28  displays the human icons  292 ,  294  in different display modes depending on the degree of risk evaluated by the attention degree evaluator  250 . Consequently, the difference between the degrees of attention of the monitored targets can be indicated to the driver for assisting in driving the vehicle  12 . The degree of risk (degree of attention) represents a possibility that a monitored target can collide with the vehicle  12 . 
       D. Modifications 
       [0186]    The present invention is not limited to the aforementioned first and second embodiments, but may employ various arrangements based on the details of the disclosure of the present invention. For example, the present invention may employ the following arrangements. 
         [0000]    [1. Objects in which the Vehicle Periphery Monitoring Apparatus can be Incorporated] 
         [0187]    In the above embodiments, the vehicle  12  is assumed to be a four-wheel vehicle (see  FIG. 2 ). However, the vehicle  12  in which the vehicle periphery monitoring apparatus  10 ,  210  can be incorporated is not limited to a four-wheel vehicle. Rather, the vehicle periphery monitoring apparatus  10 ,  210  may be incorporated in a two-wheeled vehicle (including a bicycle), a three-wheeled vehicle, or a six-wheeled vehicle. 
         [0188]    In the above embodiments, the vehicle periphery monitoring apparatus  10 ,  210  is incorporated in the vehicle  12 . However, the vehicle periphery monitoring apparatus  10 ,  210  may be incorporated in another mobile object, insofar as the device detects a monitored target in the periphery of the mobile object and indicates the detected monitored target to the user. The mobile object may be a ship or an aircraft, for example. 
       [2. Image Capturing Means] 
       [0189]    In the above embodiments, the two infrared cameras  16 L,  16 R are used as image capturing means for capturing images in the periphery of the vehicle  12 . However, the image capturing means are not limited to infrared cameras  16 L,  16 R, insofar as the image capturing means are capable of capturing images in the periphery of the vehicle  12 . For example, the image capturing means may be multiocular (stereo camera) or monocular (single camera). Instead of infrared cameras, the image capturing means may comprise cameras (color cameras), which use light having wavelengths primarily in the visible range, or may comprise both color and infrared cameras. 
       [3. General-Purpose Monitor  26  (First Display Unit) and MID  28  (Second Display Unit)] 
       [0190]    In the above embodiments, the general-purpose monitor  26  is used to display the grayscale image  72  from the infrared camera  16 L. However, any type of display unit may be used, insofar as the display unit is capable of displaying images captured by image capturing means. In the above embodiments, the highlighting frame  76  is displayed within the grayscale image  72  that is displayed on the general-purpose monitor  26 . However, the grayscale image  72  from the infrared camera  16 L may be displayed in an unmodified form on the general-purpose monitor  26  without any highlighting features added thereto. 
         [0191]    In the above embodiments, a relatively versatile display unit, which operates in a non-interlace mode, is used as the MID  28  for displaying biological icons (marks). However, a plurality of (e.g., three) indicators, which are arranged in an array for displaying only biological icons, may be used instead of the MID  28 . Alternatively, a head-up display (HUD), such as that shown in FIG. 2 of Japanese Laid-Open Patent Publication No. 2004-364112, may be used in place of the MID  28 . 
         [0192]    In the above embodiments, the general-purpose monitor  26  and the MID  28  both are used. However, only the MID  28  may be used. If only the MID  28  is used, then the grayscale image  72  acquired by the infrared camera  16 L is displayed on the MID  28 .