Patent Abstract:
A system mounted on a powered industrial vehicle for detecting classifying and tracking in real time at least one obstruction in the scene around the vehicle. The vehicle is capable of moving in multiple directions. The system includes a multiple cameras mounted on the vehicle, wherein the viewing zones viewed respectively by the cameras preferably encompass 360° horizontally around the vehicle. Each of the cameras is operatively attached to an image processor, which processes the image frames acquired respectively by the camera. When a pedestrian is present in the viewing zone viewed by one of the cameras, the image processor attached to the one camera identifies in at least one of the image frames at least a portion of an image of the detected pedestrian

Full Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application claims the benefit under 35 USC 119(e) from U.S. provisional application 60/781,652 filed Mar. 14, 2006, the disclosure of which is included herein by reference. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The present invention relates to the detecting and identifying pedestrians around a powered industrial vehicle and more particularly the present invention detects and identifies pedestrians around a powered industrial vehicle using multiple cameras that provide images of the scene, preferably in an angle 360° (angular) around the powered industrial vehicle. 
       BACKGROUND OF THE INVENTION AND PRIOR ART 
       [0003]    An operator of a powered industrial vehicle is required to notice pedestrians in the area around which the vehicle is operating. Prior art solutions for detecting pedestrians include the use of electromagnetic radiation emitters coupled with RADAR sensors, laser sensors, and/or SONAR (ultrasonic) sensors to provide the operator with some indication that a pedestrian may be present in the area around the vehicle. 
         [0004]    A significant limitation of prior art systems is in the inability to discern whether the object being detected is an insignificant inanimate object (e.g. trash, boxes, poles, etc.) or a pedestrian. As a result, prior art systems alert the industrial truck operator of the presence of every object thereby creating multiple false alarms. These false alarms annoy the operator with unnecessary warnings, and cause the operator to be less sensitive to the warnings. 
         [0005]    Furthermore, radar and laser sensors as well as ultrasound sensors have the disadvantage that in the immediate vehicle surroundings they are able to detect only a small region of the surroundings because of their small aperture angle, which typically provides a narrow FOV. Thus, a large number of sensors is required if the entire vehicle surroundings are to be detected using such sensors. 
         [0006]    An example of a laser based system, is disclosed in U.S. Pat. No. 7,164,118 (hereinafter U.S. Pat. No. &#39;118), by Anderson et al U.S. Pat. No. &#39;118 discloses a method of detecting presence of an object and the distance between the system and an object using a laser mounted on an industrial vehicle. The transmitter emits linear beams of electromagnetic radiation with a transmitted radiation pattern within a defined spatial zone. A camera collects an image of the defined spatial zone. A data processor detects a presence of an object in the collected image based on an observed illumination radiation pattern on an object formed by at least one of the linear beams. A distance estimator estimates a distance between the object and the optical device. 
         [0007]    There are also prior art systems using imaging devices to image the scene in an angle 360° horizontally around a vehicle. Such a system is disclosed in US patent application 2004/0075544 (hereinafter US &#39;544), by Janssen Holger. US &#39;544 uses two optical sensors that act as a pair of stereo cameras. The sensors are coupled with fisheye lenses, which have a very wide-angle of 220°. Thus, a large portion of the surroundings of the motor vehicle may be detected but the very wide-angle lenses provide images with a large extend of distortion, and US &#39;544 does not disclose if the distortion is corrected. In US &#39;544 all sensors emit the sensed information to a single controller. 
         [0008]    Tracking a detected pedestrian over time enables the system to detect a pedestrian at a relatively far distance from the vehicle, such as 15 meters or more, and then track the detected pedestrian with high confidence at a closer range, which might endanger the pedestrian and thus, the powered industrial vehicle driver will be warned by the system. Tracking also enables the system to stay locked on a detected pedestrian as the image of a detected pedestrian departs from a frame provided by one camera and enters a frame of an adjacent camera of the same system. Tracking of the detected pedestrian will then proceed using the second camera. 
         [0009]    There are prior art systems, mounted in vehicles, for detecting pedestrians and for measuring the distance from the vehicle to the detected pedestrian. A pedestrian detection system is described in U.S. application Ser. No. 10/599,635 (hereinafter U.S. Ser. No. &#39;635) by Shashua et al, the disclosure of which is included herein by reference for all purposes as if entirely set forth herein. U.S. Ser. No. &#39;635 provides a system mounted on a host vehicle and methods for detecting pedestrians in an image frame, the image provided by a monocular camera. 
         [0010]    A distance measurement from a visible camera image frame is described in “Vision based ACC with a Single Camera: Bounds on Range and Range Rate Accuracy” by Stein et al., presented at the IEEE Intelligent Vehicles Symposium (IV2003), the disclosure of which is incorporated herein by reference for all purposes as if entirely set forth herein. Distance measurement is further discussed in U.S. application Ser. No. 11/554,048 (hereinafter U.S. Ser. No. &#39;048) by Stein et al., the disclosure of which is included herein by reference for all purposes as if entirely set forth herein. U.S. Ser. No. &#39;048 provides methods for refining distance measurements from the vehicle hosting the distance measuring system, to an obstruction. 
         [0011]    An obstruction detection and tracking system is described in U.S. Pat. No. 7,113,867 (hereinafter U.S. Pat. No. &#39;867) by Stein, and included herein by reference for all purposes as if entirely set forth herein. Obstruction detection and tracking is performed based on information from multiple images captured in real time using a camera mounted in a vehicle hosting the obstruction detection and tracking system. 
         [0012]    The systems disclosed in U.S. Ser. No. &#39;635, U.S. Pat. No. &#39;867 and U.S. Ser. No. &#39;048, are typically part of a warning and/or control system for vehicles that are typically traveling forward on roads at relatively high speeds. They are not suitable to a powered industrial vehicle, such as a forklift, which typically travels off the road, at low speeds and in any directions. Thus, a powered industrial vehicle needs a warning system that can warn the driver of a pedestrian located anywhere near in the area around the powered industrial vehicle. 
         [0013]    Thus, there is a need for and it would be advantageous to have a system including multiple cameras mounted on a powered industrial truck, each camera equipped with an image processing system for detecting pedestrians and in the system when one camera detects a pedestrian and the pedestrian moves out of the field of view (in horizontal plane) of the one camera, data is passed to the second camera so that the pedestrian is tracked using the multiple cameras over a wide field of view. 
         [0014]    The term “powered industrial vehicle” as used herein refers to a vehicle selected from the group of vehicles including forklifts, container handlers, rubber tired gantry cranes. A powered industrial vehicle typically travels at a low speed, is capable of moving in multiple directions and frequently changes the traveling direction. 
         [0015]    The term “Field Of View” (FOV) in general is the angular extent of a given scene, delineated by the angle of a three dimensional cone that is imaged onto an image sensor of a camera, the camera being the vertex of the three dimensional cone. The FOV of a camera at particular distances is determined by the focal length of the lens: the longer the focal length, the narrower the field of view. The terms “Field Of View” of a camera and “viewing zone” of a camera are used herein interchangeably and are used herein to refer to the horizontal angular extent of a given scene, as imaged on to the image sensor of the camera. It is assumed that the dimensions of the detector are adapted to the camera FOV. 
       SUMMARY OF THE INVENTION 
       [0016]    According to the present invention there is provided a system mounted on a powered industrial vehicle for detecting classifying and tracking in real time at least one obstruction in the scene around the vehicle and method of use. The vehicle is capable of moving in multiple directions. The system includes multiple cameras mounted on the vehicle, wherein the viewing zones viewed respectively by the cameras preferably encompass 360° horizontally around the vehicle. Each of the cameras is operatively attached to an image processor, which processes the image frames acquired by the respective camera. When a pedestrian is present in the viewing zone viewed by one of the cameras, the image processor attached to the one camera identifies in at least one of the image frames at least a portion of an image of the detected pedestrian, thereby producing a detected pedestrian data object. The detected pedestrian data object includes one or more of the following features: distance, azimuth angle, size, time, color. The image processor computes the distance from the vehicle to the detected pedestrian and the azimuth to the detected pedestrian relative to the longitudinal axis of the vehicle. From a one time calibration procedure, the distance of each camera from the closest track external surface is measured and stored in the respective image processor and/or in the system processor. From a one time calibration procedure, the azimuth each camera optical axis relative to the longitudinal axis of the vehicle is measured and stored in the respective image processor and/or in the system processor. 
         [0017]    The image processor continuously tracks the detected pedestrian while updating the computed distance from the vehicle to the detected pedestrian and the azimuth to the detected pedestrian relative to the longitudinal axis of the vehicle. The image processor transfers the detected pedestrian data object to a common bus interconnecting all image processors and the system processor wherein the image processor attaches an ID code to the detected pedestrian data object. Adjacent image processors can either read the detected pedestrian data object directly from the bus or receive it from the system processor. 
         [0018]    Viewing zones of adjacent cameras are preferably overlapping. When the detected pedestrian enters an overlapping zone, i.e., the pedestrian is imaged by two adjacent cameras, respective image processors detect the obstruction, classify the obstruction as a pedestrian, measure the distance and azimuth to the detected pedestrian and continuously track the detected pedestrian. The system processor performs stereo analysis to refine the distance estimation to the detected pedestrian. The system processor notifies the vehicle operator interface on each detected pedestrian. The notification can be visual: lights, colored lights, display; and/or the notification can be audible: speakers. The speakers can be configured in a stereophonic configuration or in a surround configuration, indicating to the vehicle operator the direction to said detected pedestrian. The audible alarm to the operator is either constant in tone and/or loudness, or with a progressive increase in loudness and/or frequency as the pedestrian&#39;s proximity to vehicle decreases. The visual warning scheme can include, for example, indicating lights that turn from green to amber and from amber to red, as the pedestrian&#39;s proximity to vehicle decreases. 
         [0019]    In embodiments of the present invention, an activation mechanism is operatively attached to the system processor, the activation mechanism causing the vehicle to slow down or stop, to avoid an accident. 
         [0020]    In embodiments of the present invention, the system processor and one of the image processors are operated from a single processor. 
         [0021]    In another method of the present invention, tracking of a detected pedestrian is performed by the system processor. This requires a higher frame rate transfer on the bus, when a pedestrian is detected. 
         [0022]    In another method of the present invention, detection, classification and tracking of a detected pedestrian is performed by the system processor. This requires a much higher frame rate transfer on the bus, when a pedestrian is detected. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0023]    The present invention will become fully understood from the detailed description given herein below and the accompanying drawings, which are given by way of illustration and example only and thus not limitative of lie present invention. 
           [0024]      FIG. 1  is a perspective view of an embodiment of a pedestrian detection and tracking system of the present invention, configured with a powered industrial vehicle (in this case, a forklift vehicle). 
           [0025]      FIG. 2  is a schematic illustration of a system pedestrian detection with N cameras, according with embodiments of the present invention; 
           [0026]      FIG. 3  is a top view of an embodiment of a pedestrian detection and tracking system of the present invention configured with a forklift vehicle and a four cameras system, illustrating the viewing zones in which each camera is viewing, each viewing zone is delineated by the 90° FOV of the respective camera; 
           [0027]      FIG. 4  is a top view of an embodiment of a pedestrian detection and tracking system of the present invention configured with a forklift vehicle and a six cameras system, illustrating the viewing zones in which each camera is viewing; 
           [0028]      FIG. 5  is a top view of an embodiment of a pedestrian detection and tracking system of the present invention configured with a forklift vehicle and a six cameras system in a non-concentric configuration, illustrating the viewing zones viewed by each camera; 
           [0029]      FIG. 6  is a top view of an embodiment of a pedestrian detection and tracking system of the present invention configured with a forklift vehicle and a six cameras system, illustrating the viewing zones in which each camera is viewing, the six cameras encompassing two separate zones; 
           [0030]      FIG. 7  is a top view of a pedestrian detection and tracking system of the present invention illustrating a example of a viewing zone viewed by a camera  50   b , having a pedestrian  90  in the viewing zone; 
           [0031]      FIG. 8  is a view of an image on an image plan of the camera  50   b , as illustrated in  FIG. 7 ; 
           [0032]      FIG. 9  is a conceptual view of the operator interface/control according with embodiments of the present invention; 
           [0033]      FIG. 10  is a schematic flow diagram of a method  200  for detecting a pedestrian, in a pedestrian detection and tracking system mounted on a powered industrial vehicle, according with embodiments of the present invention; 
           [0034]      FIG. 11  is a schematic flow diagram of a method  300  for detecting a pedestrian, in a pedestrian detection and tracking system mounted on a powered industrial vehicle, according with embodiments of the present invention; 
           [0035]      FIG. 12  is a schematic flow diagram of a method  301  for detecting a pedestrian, in a pedestrian detection and tracking system mounted on a powered industrial vehicle, according with embodiments of the present invention; 
           [0036]      FIG. 13   a  illustrates a distorted image of a checkerboard pattern, as imaged through a 90° fisheye lens, used by a camera according to embodiments of the present invention; 
           [0037]      FIG. 13   b  illustrates the corrected image of the checkerboard pattern image of  FIG. 13   a , as corrected by a system of the present invention; 
           [0038]      FIG. 14   a  illustrates a distorted image of a scene, as imaged through a 90° fisheye lens, used by a camera according to embodiments of the present invention; and 
           [0039]      FIG. 14   b  illustrates the corrected image of the scene image of  FIG. 14   a , as corrected by a system of the present invention; 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0040]    The present invention is of a system mounted on a powered industrial vehicle and methods for detecting and classifying in real time an obstruction, in particular a pedestrian, around the powered industrial vehicle. The pedestrian detection and tracking system includes multiple cameras that combine to encompass the scene around the powered industrial vehicle, each camera equipped with an independent image processor. The pedestrian detection system and methods detect pedestrians in a series of image frames obtained from each camera. 
         [0041]    The principles and operation of a system and method for detecting, classifying and tracking in real time a pedestrian, in a series of images obtained from a series of cameras mounted on a powered industrial vehicle to provide a signal to warn the vehicle operator of the detected a pedestrian, according to the present invention, may be better understood with reference to the drawings and the accompanying description. 
         [0042]    Before explaining embodiments of the invention in detail, it is to be understood that the invention is not limited in its application to the details of design and the arrangement of the components set forth in the following description or illustrated in the drawings. The invention is capable of other embodiments or of being practiced or carried out in various ways. Also, it is to be understood that the phraseology and terminology employed herein is for the purpose of description and should not be regarded as limiting. 
         [0043]    By way of introduction, a principal intention of the present invention is to provide a system and method for detecting a pedestrian, preferably in an angle 360° around the vehicle. The pedestrian detection and tracking system includes a multiple number of cameras, each with a wide angle lens, that combine to encompass the scene around the vehicle, up to a range of 15 meters and more. Each camera FOV is at least tangential to the FOV of the next neighboring camera and preferable has some overlap with the FOV of the next neighboring camera. In some embodiments of the present invention, the image processing system of each camera is capable of correcting fisheye distortion of the camera lens and then detecting a pedestrian if the pedestrian appears in one or more viewing zones of the system cameras, and track the detected pedestrian over time. Tracking is maintained even if the detected pedestrian sits bends down or lies down on the floor. Tracking is maintained when the image of a detected pedestrian departs from a frame provided by one camera and enters a frame of the next neighboring camera. Tracking of the detected pedestrian will then proceed using the second camera. Upon detection of a pedestrian by the system and/or when the range of the detected pedestrian to the powered industrial vehicle is below some threshold, the driver of the vehicle is notified. 
         [0044]    Implementation of the method and system of the present invention involves performing or completing selected tasks or steps manually, automatically, or a combination thereof. Moreover, according to actual instrumentation and equipment of preferred embodiments of the method and system of the present invention, several selected steps could be implemented by hardware or by software on any operating system of any firmware or a combination thereof. For example, as hardware, selected steps of the invention could be implemented as a chip or a circuit. As software, selected steps of the invention could be implemented as a plurality of software instructions being executed by a computer using any suitable operating system. In any case, selected steps of the method and system of the invention could be described as being performed by a data processor, such as a computing platform for executing a plurality of instructions. 
         [0045]    Referring now to the drawings,  FIG. 1  is a perspective view of an embodiment of a pedestrian detection and tracking system of the present invention configured with a powered industrial vehicle  10  (e.g. a forklift vehicle) and six camera units ( 50  and  60 ) viewing the scene in an angle 360° horizontally around the vehicle. The number of six cameras is given by way of example only, and the total number of cameras may vary depending on vehicle size, camera field of view, etc. Forklift  10  (with forks  40  being in the front of the vehicle) also includes an operator system interface that is typically located in dashboard  20  of vehicle  10 , behind wheel  22 . 
         [0046]    Referring now to  FIG. 2 , a schematic illustration of a pedestrian detection and tracking system  100  with N camera units ( 57  and  60 ), according to embodiments of the present invention, is shown. System  100  also includes a processor  120  and a vehicle operator interface  30 . Each camera unit  57  includes an image sensor or camera  571 , such as a CMOS sensor, and a processor  573 . Image frames  572  are captured by camera  571 . Methods according to different embodiments of the present invention analyze in real time image frames  572 , using either processor  573  or processor  120  to detect one or more obstructions in image frames  572  and classify the detected obstructions as pedestrians. The detected pedestrian are then tracked over time, as long as a pedestrian is in the FOV of at least one camera. Processor  120  and processor  573  are a general purpose microprocessor, a processor implemented using digital signal processing (DSP) or an application specific integrated circuit (ASIC) or a combination of the different technologies. 
         [0047]    It should be noted that a one time calibration procedure is performed when the cameras  50  and  60  are installed on vehicle  10 . From a one time calibration procedure, the distance of each camera from the closest track external surface is measured and stored in the respective image processor and/or in the system processor. From a one time calibration procedure, the azimuth each camera optical axis relative to the longitudinal axis of the vehicle is measured and stored in the respective image processor and/or in the system processor. 
         [0048]    All N camera units ( 57  and  60 ) can communicate with each other and with system processor  120 , preferably over a common system data bus  70 , e.g. CAN bus, USB bus, etc. In embodiments where digitized video signals are to be transferred to system processor  120  at a high frame rate, the selected bus should be of high bandwidth. Each camera unit  57  has an identification code (ID) and all messages a camera unit  57  transmits, includes the camera&#39;s ID. Optionally, each processor  573  of camera unit  57  is programmed to which camera ID to ‘listen’ to. For example, each camera unit  57  can be programmed to ‘listen’ only to the two adjacent cameras, in order to enable the performance of continuous tracking of a detected pedestrian. 
         [0049]    System processor  120  includes a camera control unit  122  which coordinates the communication with each camera unit  57  and the inter communication among camera units  57 . System processor  120  may also include a pedestrian detector  124  and an obstruction detector  126 , which are used in a method in which detection and tracking of a pedestrian are not performed by the local image processor  573 . System processor  120  may also includes a warning/control unit  128  which issues warnings to the vehicle operator and/or control the vehicle controls, e.g. the track braking system. System processor  120  is preferably connected directly to back pointing camera  60  or to front pointing camera  50 . System processor  120  may also be integrated with one of the local image processor  573 , preferably with back pointing camera  60  or front pointing camera  50 . 
       Multiple Camera Configurations Examples 
       [0050]    Referring now to  FIG. 3 , a top view of an embodiment of a pedestrian detection and tracking system  100  of the present invention, configured with a forklift vehicle  10  and a four concentric cameras system, is shown. The viewing zones which each camera is viewing are delineated by the FOV of the respective camera: back pointing camera  60  has a FOV  601 , front pointing camera  50   a  has a FOV  501   a , right pointing camera  50   b  has a FOV  501   b  and left pointing camera  50   c  has a FOV  501   c . In the embodiment illustrated in  FIG. 3 , FOVs  601  and  501  combine to encompass 360° horizontally around vehicle  10  with generally no overlap between adjacent FOVs. The preferred FOV of each camera  571 , in a four camera configuration, is 90°, but the present invention is not limited to a 90° FOV, and any FOV angle can be used. 
         [0051]    Referring now to  FIG. 4 , a top view of an embodiment of a pedestrian detection and tracking system  100  of the present invention configured with a forklift vehicle  10  and a six concentric cameras system, are shown. The viewing zones which each camera is viewing are delineated by the FOV of the respective camera: back pointing camera  60  has a FOV  601 , front pointing camera  50   a  has a FOV  501   a , right pointing cameras  50   b  and  50   d  has a FOV  501   b  and  501   d  and left pointing cameras  50   c  and  50   c  has a FOV  501   e  and  501   e . In the embodiment illustrated in  FIG. 4  FOVs  501  and  601  combine to encompass 360° horizontally around vehicle  10  with a 30° overlap between adjacent FOVs. The preferred FOV of each camera  571 , in a four camera configuration, is 90°, but the present invention is not limited to a 90° FOV, and any FOV angle can be used. 
         [0052]    Placing N cameras in a concentric configuration is often not practical on a powered industrial vehicle, which typically has only partial housing and partial roofing. The cameras need to be placed at location such that no or minimal blocking of field of vision of a camera occur. Each camera is preferably housed in a permanent structure and placed in a protective location due to the working conditions of and around the powered industrial vehicle. Hence, the cameras are typically placed in a non-concentric configuration.  FIG. 5  is a top view of an embodiment of a pedestrian detection and tracking system  100  of the present invention configured with a forklift vehicle  10  and a six cameras system in a non-concentric configuration. The viewing zones which each camera is viewing are delineated by the FOV of the respective camera: back pointing camera  60  has a FOV  601 , front pointing camera  50   a  has a FOV  501   a , right pointing cameras  50   b  and  50   d  has a FOV  501   b  and  501   d  and left pointing cameras  50   c  and  50   c  has a FOV  501   e  and  501   e . Each adjacent pair of viewing zones overlap is reduced to about 2°. Some blind spots  80  maybe formed. Blind spots  80  are limited in range to a few feet. In the example shown in  FIG. 5  of a pedestrian detection and tracking system  100  with a four camera configuration, the FOV of each camera  571 , is 90°, but the present invention is not limited to a 90° FOV, and any FOV angle can be used. 
         [0053]    The present invention preferably encompasses 360° horizontally around vehicle  10  with an overlap between adjacent FOVs. But in some embodiments of the present invention, pedestrian detection and tracking system  100  may encompass and area horizontal angle less than 360°.  FIG. 6  is a top view of an embodiment of a pedestrian detection and tracking system  100  of the present invention configured with a forklift vehicle  10  and a six cameras system, illustrating the viewing zones in which each camera is viewing, the six cameras encompassing two separate zones. This configuration is given by way of example only and other configurations encompass and area horizontal angle less than 360° are possible and are within the scope of the present invention. 
       Vehicle Operator Interface 
       [0054]    Pedestrian detection and tracking system  100  also includes a vehicle operator interface unit  30 , which is typically located in dashboard  20  of vehicle  10 , behind wheel  22 .  FIG. 9  is an example illustration of a vehicle operator interface/control  30  according to embodiments of the present invention. Interface  30  may include visual and/or audible indication to alert the operator on the presence of a pedestrian in the vicinity of vehicle  10 . In the example of  FIG. 9 , interface  30  includes a display  32  presenting the cameras viewing zones, and light indicators  34 , for example green red and amber, indicating the danger level to a detected pedestrian in vehicle  10  vicinity. When a pedestrian is detected, the corresponding zone of display  32 , representing the zone around vehicle  10  in which the pedestrian is located, may, for example, turn on, change color or provide any other type of indication. 
       Methods of the Present Invention 
       [0055]    Referring back to  FIG. 2  and also referring now to  FIG. 10 , which is a schematic flow diagram of a method for detecting a pedestrian, in a pedestrian detection and tracking system  100  mounted on a powered industrial vehicle  10 , according with embodiments of the present invention. In method  200 , when vehicle  10  is operated, pedestrian detection and tracking system  100  starts monitoring the scene in an angle 360° horizontally around vehicle  10  (step  210 ) with N camera units ( 57  and  60 ). Upon the entering of a pedestrian into a zone viewed by an image sensor  571  of camera unit  57 , the image frames  572 , which include the images of the pedestrian, are transmitted to respective image processor  573 . Image processor  573  analyzes image frames  572  and detects the pedestrian (step  220 ), thereby producing a detected pedestrian. The distance and azimuth from vehicle  10  to the pedestrian are computed (step  222 ) and system processor  120  is notified (step  260 ). System processor  120  in turn notifies the vehicle operator and possibly other bodies, such as a control center (step  270 ). Image processor  573  tracks the detected pedestrian (step  224 ), using camera unit  57 , while continuing computing the distance and azimuth from vehicle  10  to the detected pedestrian. The two adjacent camera units  57  are notified by system processor  120  about the detected pedestrian being detected tracked by camera unit  57 . 
         [0056]    Upon the entering of the pedestrian also into a zone viewed by the image sensor of a camera unit adjacent to camera unit of camera unit  57 , image processor  573  of the adjacent camera unit  57  analyzes respective image frames  572  received from image processor  573  of the adjacent camera unit  57 . Image processor  573  of the adjacent camera unit  57  detects the pedestrian (step  230 ), thereby also producing a detected pedestrian data object. The distance and azimuth from vehicle  10  to the pedestrian are computed (step  232 ) and system processor  120  is notified (step  260 ). Image processor  573  of the adjacent camera unit  57  starts tracking the detected pedestrian (step  234 ), using the adjacent camera unit  57 , while continuing computing the distance and azimuth from vehicle  10  to the detected pedestrian. When there is an overlap of the zone viewed by the image sensor of a camera unit  57  and the zone viewed by the image sensor of the adjacent camera unit  57 , stereo analysis is performed by system processor  120  to refine the distance estimation to the twice detected pedestrian (step  240 ). The results of the stereo analysis are synchronized by system processor  120  with the image processors  573  of the two camera units  57 . When the pedestrian drops out of the zone viewed by one of the image sensors  571 , tracking proceeds using the other camera unit  57  (step  260 ). As tracking continuous and the distance and/or azimuth to the detected pedestrian are changing, system processor  120  is notified and in turn, the vehicle operator is updated (step  270 ). In the following description, method steps of method  200  are discussed in further detail. 
         [0057]    Step  210 : Monitor the scene in an angle 360° horizontally around the vehicle. 
         [0058]    A power industrial vehicle  10  is typically a vehicle that can travel in any direction and rapidly change the direction of travel. But the operator of vehicle  10  stays in the same orientation, relative to vehicle  10 , not being able to continuously view all the area around vehicle  10 , a set of cameras are positioned on vehicle  10  to continuously monitor the scene in an angle 360° horizontally around vehicle  10 , up to a range of 15 meters and more, using N camera units ( 57  and  60 ). In a preferred embodiment, six camera units are used (N=6). Camera units ( 57  and  60 ) are positioned in a protected location in the periphery of vehicle  10 . Viewing zones of adjacent cameras  50  preferably overlap in horizontal angle and at least tangential. In a non-concentric six camera configuration, each camera  50  preferably has a 90° FOV and the viewing zones overlap of about 20° in horizontal angle. 
         [0059]    Step  220 : Detect pedestrian by camera unit  57 . 
         [0060]    Upon the entering of a pedestrian into a viewing zone viewed by an image sensor  571  of camera unit  57 , image frames  572  including the pedestrian image are transmitted to respective image processor  573 . Image processor  573  analyzes image frames  572  and detects the pedestrian, thereby producing a detected pedestrian data object. Detection is made at a distance ranging from 1.5 meters and up to 15 meters and more. At a distance below 10 meter, not the whole body of a pedestrian is in the viewing zone of a camera. 
         [0061]    Step  222 : Compute distance and azimuth to pedestrian. 
         [0062]    Image processor  573  computes the distance from vehicle  10  to the detected pedestrian. U.S. Ser. No. &#39;048 provides methods for computing and refining distance measurements from a vehicle hosting the distance measuring system, to an obstruction, including pedestrians.  FIG. 7  is a top view of a pedestrian detection and tracking system  100  of the present invention illustrating an example of a viewing zone viewed by the image sensor of camera unit  50 , having a pedestrian  90  in the viewing zone.  FIG. 8  is a view of a corrected image  450  on an image plan of image sensor of camera unit  50 , as illustrated in  FIG. 8 . Image  450  includes a detected pedestrian  490  with a rectangle  492  enclosing detected pedestrian  490 . Each image processor  573  knows the distance of respective image sensor of camera unit  50  from the local external surface of vehicle  10  and computes the distance to the bottom of rectangle  492 . Distance measurement is performed as described in U.S. Ser. No. &#39;048. Image processor  573  also knows the azimuth φ of the optical axis of image sensor of camera unit  50  and the pixel P(x j , y j ) which represents the optical axis in image  450 . The azimuth θ to pedestrian  90  is computed from the displacement d in the image of detected pedestrian  490  relative to P(x j , y j ) and from the known angle φ between the optical axis  52   b  of the image sensor of camera unit  50  and the longitudinal axis  12  of vehicle  10 . 
         [0063]    Step  224 : Track detected pedestrian  490  and monitor distance. 
         [0064]    Pedestrian tracking is performed as described in U.S. Pat. No. &#39;867. Image processor  573  continuously tracks detected pedestrian  490  in image  450  as the image of detected pedestrian  490  changes the position inside image  450 , as both pedestrian  90  and vehicle  10  are changing the spatial positions. As pedestrian  90  and vehicle  10  are changing spatial positions, image processor  573  continuously re-computes the distance from vehicle  10  to pedestrian  90  and the azimuth to pedestrian  90  relative to vehicle  10 . Although detection is not ensured when the distance of a pedestrian  90  form vehicle  10  is below 1.5 meters, but tracking is maintained down to a distance of at least 1 meter. 
         [0065]    Tracking is maintained even if pedestrian  90  sits down, bends down or lies down on the floor. Tracking is also maintained when the image of a detected pedestrian  490  departs from an image frame  572  provided by an image sensor  571  and enters the image frame  572  of the next neighboring camera  571 . Tracking of the detected pedestrian  490  will then proceed using the second image sensor  571 . 
         [0066]    Step  230 : Detect pedestrian by a neighbor camera unit. 
         [0067]    When a pedestrian  90  enters a zone viewed by a second adjacent image sensor, image processor  573  of the adjacent camera unit  57  analyzes respective image frames  572  and detects pedestrian  490  as was done by image processor  573  in step  220 . 
         [0068]    Step  232 : Compute distance and azimuth to pedestrian by the neighbor camera unit. 
         [0069]    Image processor  573  of neighbor camera unit  57  computes the distance and azimuth to pedestrian  90  as was done by image processor  573  in step  222 . 
         [0070]    Step  234 : Track detected pedestrian  490  and monitor distance by the neighbor camera unit. 
         [0071]    Image processor  573  of neighbor camera unit  57  continuously tracks and re-computes the distance and azimuth to pedestrian  90  as was done by image processor  573  in step  224 . 
         [0072]    Step  240 : Refine distance estimation using stereo analysis. 
         [0073]    When a pedestrian  90  enters a zone viewed by two adjacent image sensors  571 , image processor  573  employs stereo analysis to refine the measured distance from the external surface of vehicle  10  to pedestrian  90 . The stereo analysis to refine the distance estimation to the twice detected pedestrian (step  240 ), is performed by system processor  120 . The results of the stereo analysis are synchronized by system processor  120  and image processors  573  performing the detection and tracking. 
         [0074]    Step  250 : Continue tracking by the neighboring camera unit. 
         [0075]    When a pedestrian  90  departs the zone viewed image sensor  571  and remains only in the zone viewed by adjacent image sensor  571 , only the respective image processor  573  continuous to track and to re-computes the distance and azimuth to pedestrian  90 . 
         [0076]    Step  260 : Notify system processor. 
         [0077]    When an image processor  573  detects an obstruction and classifies the obstruction as a pedestrian  90 , image processor  573  notifies on the detected pedestrian  490  to system processor  120 . The notification message also includes an identification code, to enable system processor  120  to identify the sending camera unit  57 . System processor  120  prepares the two adjacent camera units  57  for the possibility that pedestrian  90  will enter the camera units  57  viewing zones. System processor  120  is updated when tracking of a detected pedestrian  490  is established or stopped. System processor  120  is also continuously updated as to the distance and azimuth from the external surface of vehicle  10  to pedestrian  90 . 
         [0078]    Step  270 : Notify the vehicle operator, control center. 
         [0079]    When an image processor  573  detects pedestrian  90  and notifies system processor  120 , system processor  120  notifies the vehicle operator by activating the proper indicators in operator interface  30 , the indicators being visual and/or audible. The notification to the vehicle operator may be performed according to a pre-designed warning schemer, e.g., the audible alarm to the operator is either constant in tone and loudness, or with a progressive increase in loudness and frequency as the pedestrian&#39;s  90  proximity to vehicle  10  decreases. The visual warning scheme can include, for example, indicating lights that turn from green to amber and from amber to red, as the pedestrian&#39;s  90  proximity to vehicle  10  decreases. The audio warning can be stereophonic, or surround or directional in any other way, such that it indicates the relative position of the detected pedestrian. 
         [0080]    It should be noted that system processor  120  may not only notify the vehicle operator but also operate controls of vehicle  10 , e.g. activate vehicle  10  brakes and/or reduce engine power, to avoid an accident. 
         [0081]    Reference is also now made to  FIG. 11 , which is a schematic flow diagram of a method for detecting a pedestrian  90 , in a pedestrian detection and tracking system  100  mounted on a powered industrial vehicle  10 , according with other embodiments of the present invention. It should be noted that in order for method  300  to perform in real time, bus  70  (see  FIG. 2 ) must accommodate the required transferred rate of video images from processors  573  to system processor  120 . 
         [0082]    In method  300 , when vehicle  10  is operated, pedestrian detection and tracking system  100  starts monitoring the scene in an angle 360° horizontally around vehicle  10  (step  310 ). Upon entering of a pedestrian  90  into a zone viewed by an image sensor  571  of camera unit  57  (step  320 ), respective image processor  573  analyzes respective image frames  572  and detects the pedestrian  490  (step  330 ), thereby producing a detected pedestrian data object. Optionally, image processor  573  also computes the distance and azimuth from vehicle  10  to detected pedestrian  490  (step  340 ). 
         [0083]    The detected pedestrian data object, which may include the images including detected pedestrian  490 , computed distance and azimuth aid camera unit  57  ID, are transmitted by image processor  573  to system processor  120  (step  350 ). The distance and azimuth from vehicle  10  to pedestrian  90  are computed (step  360 , if not computed in step  340 ). The vehicle operator and/or other bodies, such as a control center, are then notified (step  390 ). System processor  120  starts tracking the detected pedestrian  490  (step  370 ), using camera unit  57 , while continuing computing the distance and azimuth from vehicle  10  to pedestrian  90  (step  360 ). Any change in distance or azimuth is reported (step  390 ). 
         [0084]    The two adjacent camera units  57  are notified by system processor  120  that detected pedestrian  490  is being tracked, using camera unit  57 . Upon entering of pedestrian  90  into a zone viewed by a neighboring camera unit of camera unit  57  (step  322 ), respective image processor  573  analyzes respective image frames  572  and detects the pedestrian  490  (step  332 ), thereby producing a detected pedestrian data object. Optionally, image processor  573  also computes the distance and azimuth from vehicle  10  to detected pedestrian  490  (step  342 ). The detected pedestrian data object is transmitted by image processor  573  to system processor  120  (step  350 ). 
         [0085]    System processor  120  performs stereo analysis to refine the distance estimation to the detected pedestrian  490  (step  380 ). When pedestrian  90  drops out of the zone viewed by image sensor  571 , tracking proceeds using the adjacent camera unit  573  (step  370 ), which pedestrian  90  is in the respective image sensor  572  viewing zone. As tracking continuous and the distance and/or azimuth to pedestrian  90  are changing, the vehicle operator is updated (step  390 ). 
         [0086]    Reference is also now made to  FIG. 12 , which is a schematic flow diagram of a method for detecting a pedestrian  90 , in a pedestrian detection and tracking system  100  mounted on a powered industrial vehicle  10 , according with other embodiments of the present invention. It should be noted that in order for method  301  to perform in real time, bus  70  (see  FIG. 2 ) must accommodate the required transferred rate of video images from processors  573  to system processor  120 . 
         [0087]    In method  301 , when vehicle  10  is operated, pedestrian detection and tracking system  100  starts monitoring the scene in an angle 360° horizontally around vehicle  10  (step  311 ). Upon entering of a pedestrian  90  into a zone viewed by an image sensor  571  of camera unit  57  (step  321 ), the image frames  572 , which include the images of pedestrian  90 , are transmitted by respective processor  573  to system processor  120  (step  341 ). System processor  120  analyzes image frames  572  and detects the pedestrian (step  351 ), thereby producing a detected pedestrian. The distance and azimuth from vehicle  10  to pedestrian  90  are computed (step  361 ) and the vehicle operator and/or other bodies, such as a control center, are notified (step  391 ). System processor  120  starts tracking the detected pedestrian  490  (step  371 ), using camera unit  57 , while continuing computing the distance and azimuth from vehicle  10  to pedestrian  90 . Any change in distance or azimuth is reported (step  391 ). The two adjacent camera units  57  are notified by system processor  120  that detected pedestrian  490  is being tracked, using camera unit  57 . Upon entering of pedestrian  90  into a zone viewed by a neighboring camera unit of camera unit  57 , stereo analysis is used to refine the distance estimation to the detected pedestrian  490  (step  381 ). When pedestrian  90  drops out of the zone viewed by image sensor  571 , tracking proceeds using the adjacent camera unit  573  (step  371 ) which pedestrian  90  is in the respective image sensor  572  viewing zone. As tracking continuous and the distance and/or azimuth to pedestrian  90  are changing, the vehicle operator is updated (step  391 ). 
       Distortion Correction 
       [0088]    In order to be able to continuously monitor the scene in an angle 360° horizontally around vehicle  10 , pedestrian detection and tracking system  100  of the present invention utilizes N camera unit  57 , where in the preferred embodiment, N=6 Still, to maintain some overlap between viewing zones formed by the FOV of each adjacent pair of cameras, a 90° FOV is needed. A 90° FOV implies using wide-angle lenses which deform the images obtained by the camera by a large extend of distortion. 
         [0089]    Reference is now made to  FIGS. 13   a  and  13   b .  FIG. 13   a  illustrates a distorted image  400  of a checkerboard pattern, as imaged through a 90° fisheye lens, used by a camera  571  according to embodiments of the present invention.  FIG. 13   b  illustrates the corrected image  401  of the checkerboard pattern of  FIG. 13   a . The corrected image  401  of the checkerboard pattern demonstrates the extent of the distortion of the distorted image  400  of a checkerboard pattern. The corrected image  401  of the checkerboard pattern demonstrates the ability of pedestrian detection and tracking system  100  to correct the distortion. 
         [0090]    Reference is also now made to  FIGS. 14   a  and  14   b .  FIG. 14   a  illustrates a distorted image  410  of a scene, as imaged through a 90° fisheye lens, used by a camera according to embodiments of the present invention.  FIG. 14   b  illustrates the corrected image  411  of the scene image of  FIG. 14   a . Pedestrian  420  is tracked in the corrected image  411 , as illustrated by rectangle  422 . It should be noted the optical distortion is fixed per each individual system and needs to be measured only once in a system lifetime to derive its optical correction equation. 
         [0091]    In embodiments of the present invention, pedestrian detection and tracking system  100  is mounted and operated on powered military vehicles. 
         [0092]    In embodiments of the present invention, pedestrian detection and tracking system  100  is fused with a SONAR obstruction detection system, whereby the confidence of pedestrian detection is enhanced. The SONAR obstruction detection system comprises one or more ultrasonic transmitters and one or more sensors, whereas the fusion of information obtained from pedestrian detection and tracking system  100  and the SONAR obstruction detection system, is performed by either one or more processors  573  or by system processor  120 . 
         [0093]    In embodiments of the present invention, pedestrian detection and tracking system  100  is fused with a FIR (Far Infra-Red) obstruction detection system, whereby the confidence of pedestrian detection is enhanced. The FIR obstruction detection system comprises one or more FIR image sensors, whereas the fusion of information obtained from pedestrian detection and tracking system  100  and the FIR obstruction detection system, is performed by either one or more processors  573  or by system processor  120 . 
         [0094]    Therefore, the foregoing is considered as illustrative only of the principles of the invention. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the invention to the exact design and operation shown and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope of the invention. 
         [0095]    While the invention has been described with respect to a limited number of embodiments, it will be appreciated that many variations, modifications and other applications of the invention may be made.

Technology Classification (CPC): 6