Patent Publication Number: US-2005128291-A1

Title: Video surveillance system

Description:
This application is a continuing application, filed under 35 U.S.C. §111(a), of International Application PCT/JP02/03840, filed Apr. 17, 2002. 
    
    
     BACKGROUND OF THE INVENTION  
      1. Field of the Invention  
      The present invention relates to a surveillance system, and more particularly to a surveillance system which performs video monitoring.  
      2. Description of the Related Art  
      Many of the existing video surveillance systems use multiple fixed cameras to observe a particular area and allow an operator to check the camera views on a video monitor screen. Some recent systems have automatic tracking functions to keep track of a moving object found in the acquired video images while changing the camera direction by controlling the rotator on which the camera is mounted.  
      Cameras suitable for surveillance purposes include high-sensitivity visible-light cameras and infrared cameras. As an example of a conventional system, Japanese Patent Application Publication No. 11-284988 (1999) describes the combined use of those different types of cameras. The system disclosed in this publication employs an infrared camera to detect an intruder and determine its movement direction. Based on that information, the system controls a visible-light camera such that the intruder comes into its view range. This control technique enables automatic tracking of an intruder even in a dark environment.  
      One drawback of the above-described conventional system, however, is that it requires in nighttime a light source like floodlights for a visible-light camera to form an image of an intruder. The use of lighting would increase the chance for an intruder to notice the presence of surveillance cameras.  
      Another drawback is that, since the visible-light camera does not move until an intruder is actually detected, the system may allow the intruder to pass the surveillance area without being noticed or lose sight of the intruder halfway through the tracking task. Yet another drawback of the proposed system is the lack of object discrimination functions. The camera sometimes follows an irrelevant object such as vehicles, thus missing real intruders.  
     SUMMARY OF THE INVENTION  
      In view of the foregoing, it is an object of the present invention to provide a video surveillance system that automatically keeps track of moving object in an accurate and efficient manner.  
      To accomplish the above object, the present invention provides a video surveillance system. This system comprises the following elements: (a) a visible-light integrating camera having frame integration functions for taking visible-light video; (b) an infrared camera for taking infrared images; (c) a tracking controller comprising a rotation unit that rotates the visible-light integrating camera or infrared camera, and an image processor that processes video signals supplied from the visible-light integrating camera or the infrared camera; and (d) a system controller that commands the tracking controller to keep track of a moving object by using the visible-light integrating camera in a first period and the infrared camera in a second period.  
      The visible-light integrating camera takes visible-light video using its frame integration functions, while the infrared camera takes infrared video. The rotation unit rotates the visible-light integrating camera or infrared camera. The image processor processes video signals supplied from the visible-light integrating camera or infrared camera. The system controller commands the tracking controller to keep track of a moving object by using the visible-light integrating camera in a first period and the infrared camera in a second period.  
      The above and other objects, features and advantages of the present invention will become apparent from the following description when taken in conjunction with the accompanying drawings which illustrate preferred embodiments of the present invention by way of example. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       FIG. 1  is a conceptual view of a surveillance system according to the present invention.  
       FIG. 2  shows the concept of frame integration processing that a visible-light integrating camera performs.  
      FIGS.  3  to  5  show a specific structure of a surveillance system.  
       FIG. 6  shows relative locations of a moving object and a camera.  
       FIG. 7  shows a coordinate map used in prediction of a new object position.  
       FIG. 8  shows how two cameras are used in tracking and waiting operations.  
       FIG. 9  shows the structure of an image processor and a moving object discriminator.  
       FIG. 10  shows calculation of the length-to-width ratio of a labeled group of pixels.  
       FIG. 11  shows a movement path map.  
       FIG. 12  shows a variation of the surveillance system according to the present invention. 
    
    
     DESCRIPTION OF THE PREFERRED EMBODIMENTS  
      Preferred embodiments of the present invention will be described below with reference to the accompanying drawings, wherein like reference numerals refer to like elements throughout.  
       FIG. 1  is a conceptual view of a surveillance system according to the present invention. This surveillance system  1 , falling under the categories of industrial TV (ITV) systems or security systems, is designed for video surveillance with a capability of automatically tracking moving objects (e.g., humans).  
      The surveillance system  1  has two cameras. One is a visible-light integrating camera C 1  having a frame integration function to capture visible-light images of objects. The other is an infrared camera C 2  that takes images using infrared radiation from objects.  
      Also provided is a tracking controller  100 , which includes a rotation unit  101  and an image processor  102 . The rotation unit  101  (hereafter “rotator driver”) controls either or both of two rotators  31  and  32 , on which the visible-light integrating camera C 1  and infrared camera C 2  are mounted, respectively. The image processor  102  processes video signals from either or both of the visible-light integrating camera C 1  or infrared camera C 2 .  
      The tracking controller  100  is controlled by a system controller  40  in such a way that, in tracking moving objects, the visible-light integrating camera C 1  will work during a first period (e.g., daytime hours) and the infrared camera C 2  will work during a second period (e.g., nighttime hours). The system controller  40  also receives visible-light video signals from the visible-light integrating camera C 1 , as well as infrared video signals from the infrared camera C 2 , for displaying camera views on a monitor unit  54 .  
       FIG. 2  shows the concept of frame integration processing that a visible-light integrating camera performs. Frame integration is a process of smoothing video pictures by adding up pixel values over a predetermined number of frames and then dividing the sum by that number of frames. Consider an integration process of 30 frames, for example. The pixel values (e.g., g 1  to g 30 ) at a particular point are added up over 30 frames f 1  to f 30 , and the resulting sum is divided by 30. The integration process repeats such computation for every pixel constituting a frame, thereby producing one averaged frame picture. The next frame f 31  becomes available after the passage of one frame interval Δt, which triggers another cycle of integration with frames f 2  to f 31 . The frame integration technique increases effectively the sensitivity (minimum illuminance) of cameras. Thus the visible-light integrating camera C 1  can pick up images in low-light situations.  
      The visible-light integrating camera C 1  changes its operating mode to integration mode automatically when the illuminance level is decreased in nighttime hours. Since it averages over a period of time, the frame integration processing causes a slow response or produces afterimages of a moving object. According to the present invention, the system enables the infrared camera C 2 , instead of the visible-light integrating camera C 1 , during nighttime hours, so that those two different cameras will complement each other.  
     Surveillance Operation  
      This section describes detailed structure and operation of the surveillance system  1  according to the present invention. FIGS.  3  to  5  give a more specific surveillance system  1   a  in which the above-described surveillance system  1  is combined with a network  200 . This system  1   a  is largely divided into two parts. Shown at the left of the network  200  (see  FIG. 5 ) are video surveillance functions, and shown at the right are video monitoring functions.  
      The video surveillance functions include a visible-light integrating camera C 1 , a first rotator  31  for tilting and panning the camera C 1 , a first tracking controller  10  for controlling the direction of the camera C 1 , an infrared camera C 2 , a second rotator  32  for tilting and panning the camera C 2 , a second tracking controller  20  for controlling the direction of the camera C 2 , and a system controller  40  for supervising the two tracking controllers  10  and  20 . The video monitoring functions include a network interface  51 , a system coordinator  52 , a picture recording device  53 , and a monitor unit  54 .  
      During daylight hours, the surveillance system  1   a  operates as follows. A tracking setup unit  44  in the system controller  40  has a sunlight table T containing information about sunlight hours, which vary according to the changing seasons. The tracking setup unit  44  consults this sunlight table T to determine whether it is day or night. When it is determined to be daytime, the tracking setup unit  44  sends a tracking ON command signal to a first image processor  12  and a tracking OFF command signal to a second image processor  22 - 1 .  
      When a moving object (which is possibly an intruder) enters the range of the visible-light integrating camera C 1 , the first image processor  12  processes visible-light video signals from the camera C 1  to determine the object location, thus commanding a first rotator driver  11  to rotate the camera C 1  such that the captured object image will be centered in its visual angle. With this rotation command, the first rotator driver  11  controls the first rotator  31  accordingly, so that the visible-light integrating camera C 1  will track the intruder. The current position of the first rotator  31  (or of the visible-light integrating camera C 1 ) is fed back to the first image processor  12  through the first rotator driver  11 .  
      Following the object movement, the first image processor  12  supplies a first object location calculator  41   a  with image processing result signals, which include an intrusion alarm and rotation parameters. The rotation parameters includes tilt and pan angles of the camera being used. Each time new image processing result signals are received, the first object location calculator  41   a  plots the current object position on a coordinate map representing the tracking area. Two such positions on the map permit the first object location calculator  41   a  to predict the next position of the moving object and supply a second rotation controller  43   b  with the predicted position data. Details of this position prediction will be discussed later with reference to FIGS.  6  to  8 .  
      The second rotation controller  43   b  calculates tilt and pan angles of the predicted position from given data and sends the resulting rotation parameters to the second rotator driver  21 . The second rotator driver  21  activates the second rotator  32  according to those rotation parameters, thus directing the infrared camera C 2  to the predicted object position. At that position, the infrared camera C 2  waits for an object to come into view, while delivering infrared video signals to a network interface  46 .  
      Also sent to the network interface  46  is visible-light video signals of the visible-light integrating camera C 1 . After being compressed with standard video compression techniques (e.g., JPEG, MPEG), those visible-light and infrared video signals are supplied to a picture recording device  53  and monitor unit  54  via the network  200  and a network interface  51  for the purposes of video recording and visual monitoring.  
      The first object location calculator  41   a  produces a picture recording request upon receipt of image processing result signals from the first image processor  12 . This picture recording request reaches a system coordinator  52  through the local network interface  46 , network  200 , and remote network interface  51 . The system coordinator  52  then commands the picture recording device  53  to record videos supplied from the visible-light integrating camera C 1  and infrared camera C 2 .  
      The image processing result signals (including intrusion alarm and rotation parameters) are also sent from the first image processor  12  to the first movement path analyzer  42   a  at the same time as they are sent to the first object location calculator  41   a . With the given rotation parameters, the first movement path analyzer  42   a  plots the path on a first movement path map m 1 , which is a two-dimensional coordinate plane, thereby recording movements of ordinary moving objects in the surveillance area. When frequent traces of objects are observed in particular blocks on the map m 1 , the operator designates these blocks as mask blocks.  
      New intrusion alarms and rotation parameters supplied from the first image processor  12  may be of an object that falls within such mask blocks. If this is the case, the first movement path analyzer  42   a  sends a tracking cancel signal C 1   a  to the first image processor  12  not to bother to perform unnecessary tracking. The first image processor  12  thus only tracks objects existing out of those mask blocks. Details of this movement path analysis will be described later with reference to  FIG. 11 .  
      The third image processor  22 - 2 , on the other hand, analyzes given infrared video signals with a course of image processing to recognize the shape of and count pixels of each labeled object in the way described later with reference to  FIG. 9 . The result is sent to a moving object discriminator  45  as image processing result signals for discriminating moving objects. The moving object discriminator  45  then discriminates moving objects on the basis of their respective length-to-width ratios and numbers of pixels, and if the object in question falls out of the scope of surveillance, it sends a tracking cancel signal C 1   b  to the first image processor  12 . For example, a tracking cancel signal C 1   b  is generated if the moving object is not a human object. Details of this object discrimination process will be described later with reference to  FIGS. 9 and 10 .  
      The first image processor  12  stops tracking when a tracking cancel signal C 1   a  is received from the first movement path analyzer  42   a , or when a tracking cancel signal C 1   b  is received from the moving object discriminator  45 . The first image processor  12  then issues appropriate rotation parameters that command the first rotator driver  11  to return the first rotator  31  to its home position, thus terminating the series of tracking tasks.  
      During nighttime hours, the video surveillance system operates as follows. The tracking setup unit  44  consults sunlight table T to determine whether it is day or night. When it is determined to be nighttime, the tracking setup unit  44  sends a tracking OFF command signal to the first image processor  12  and a tracking ON command signal to the second image processor  22 - 1 .  
      When a moving object (which is possibly an intruder) enters the range of the infrared camera C 2 , the second image processor  22 - 1  processes infrared video signals from the camera C 2  to determine the object location, thus commanding the second rotator driver  21  to rotate the camera C 2  such that the captured object image will be centered in its visual angle. With this rotation command, the second rotator driver  21  controls the second rotator  32  accordingly, so that the infrared camera C 2  will track the intruder. The current position of the second rotator  32  (or of the infrared camera C 2 ) is fed back to the second image processor  22 - 1  through the second rotator driver  21 .  
      Following the object movement, the second image processor  22 - 1  supplies the second object location calculator  41   b  with image processing result signals, which include an intrusion alarm and rotation parameters. The rotation parameters includes tilt and pan angles of the camera being used. Each time new image processing result signals are received, the second object location calculator  41   b  plots the current object position on a coordinate map representing the tracking area. Two such positions on the map permit the second object location calculator  41   b  to predict the next position of the moving object and supply the first rotation controller  43   a  with the predicted position data. Details of this position prediction will be described later with reference to FIGS.  6  to  FIG. 8 .  
      The first rotation controller  43   a  calculates tilt and pan angles of the predicted position from given data and sends the resulting rotation parameters to the first rotator driver  11 . The first rotator driver  11  activates the first rotator  31  according to the given rotation parameters, thus directing the visible-light integrating camera C 1  to the predicted object position. At that position, the visible-light integrating camera C 1  waits for an object to come into view, while delivering visible-light video signals to the network interface  46 . As in the case of daytime, infrared video signals from the infrared camera C 2  are also compressed and supplied to the network interface  46 , for delivery to the picture recording device  53  and monitor unit  54 .  
      The second object location calculator  41   b  produces a picture recording request upon receipt of image processing result signals from the second image processor  22 - 1 . This picture recording request reaches the system coordinator  52  through the local network interface  46 , network  200 , and remote network interface  51 . The system coordinator  52  then commands the picture recording device  53  to record videos supplied from the visible-light integrating camera C 1  and infrared camera C 2 .  
      The image processing result signals (including intrusion alarm and rotation parameters) are also sent from the second image processor  22 - 1  to the second movement path analyzer  42   b  at the same time as they are sent to the second object location calculator  41   b . With the given rotation parameters, the second movement path analyzer  42   b  plots the path on a second movement path map m 2 , which is a two-dimensional coordinate plane, thereby recording movements of ordinary moving objects in the surveillance area. When frequent traces of objects are observed in particular blocks on the map m 2 , the operator designates these blocks as mask blocks.  
      New intrusion alarms and rotation parameters supplied from the second image processor  22 - 1  may be of an object that falls within such mask blocks. If this is the case, the second movement path analyzer  42   b  sends a tracking cancel signal C 2   a  to the second image processor  22 - 1  not to bother to perform unnecessary tracking. The second image processor  22 - 1  thus only tracks objects existing out of those mask blocks. Details of this movement path analysis will be described later with reference to  FIG. 11 .  
      The third image processor  22 - 2 , on the other hand, analyzes the obtained infrared video with a course of image processing to recognize the shape of and count pixels of each labeled object in the way described later with reference to  FIG. 9 . The result is sent to the moving object discriminator  45  as image processing result signals for discrimination of moving objects. The moving object discriminator  45  then discriminates moving objects on the basis of their respective length-to-width ratios and numbers of pixels, and if the object in question is not the subject of surveillance, it sends a tracking cancel signal C 2   b  to the second image processor  22 - 1 . Details of this object discrimination process will be described later with reference to  FIGS. 9 and 10 .  
      The second image processor  22 - 1  stops tracking when a tracking cancel signal C 2   a  is received from the second movement path analyzer  42   b , or when a tracking cancel signal C 2   b  is received from the moving object discriminator  45 . The second image processor  22 - 1  then issues appropriate rotation parameters that command the second rotator driver  21  to return the second rotator  32  to its home position, thus terminating the series of tracking tasks.  
      When a moving object is captured by the visible-light integrating camera C 1  or infrared camera C 2 , the corresponding image processor  12  or  22 - 1  alerts the corresponding object location calculator  41   a  or  41   b  by sending an intrusion alarm. This intrusion alarm may be negated after a while, meaning that the camera has lost sight of the object. To handle such situations, the object location calculators  41   a  and  41   b  may be designed to trigger an internal timer to send a wait command (not shown) to the corresponding image processors  12  and  22 - 1  to wait for a predetermined period. The wait command causes the visible-light integrating camera C 1  or infrared camera C 2  to zoom back to a predetermined wide-angle position and keep its lens face toward the point at which the object has been lost for the predetermined period. If the intrusion alarm comes back during this period, the camera C 1  or C 2  will be controlled to resume tracking. If the wait command expires with no intrusion alarms, the camera C 1  or C 2  goes back to a preset position that is previously specified by the operator. With this control function, the system can keep an intruder under surveillance.  
     Object Motion Prediction  
      This section explains the first and second object location calculators  41   a  and  41   b  (collectively referred to as the object location calculator  41 ) in greater detail. The object location calculator  41  predicts the position of a moving object from given image processing result signals (intrusion alarm and rotation parameters). More specifically, the object location calculator  41  maps the tilt and pan angles of a camera onto a two-dimensional coordinate plane. It then calculates the point where the object is expected to reach in a specified time, assuming that the object keeps moving at a constant speed.  
       FIG. 6  shows relative locations of a moving object and a camera.  FIG. 7  shows a coordinates map used in calculation of a predicted object position. Suppose now that the camera C has caught sight of an intruder at point A. The camera C then turns to the intruder, so that the object image will be centered in the view area. Tilt angle % a and pan angle θa of the camera rotator at this state are sent to the object location calculator  41  through a corresponding image processor. Since the height h of the camera C is known, the object location calculator  41  can calculate the distance La of the intruder (currently at point A) according to the following formula (1). The point A is then plotted on a two-dimensional coordinate plane as shown in  FIG. 7 . 
   La =tan(λ a )· h   (1)  
 A new intruder position B after a unit time is calculated in the same way, from a new tilt angle λb and pan angle θb. Specifically, the following formula (2) gives the distance Lb: 
   Lb =tan(λ b )· h   (2)  
 The calculated intruder positions are plotted at unit intervals as shown in  FIG. 7 , where two vectors La and Lb indicate that the intruder has moved from point A to point B. Then assuming that the intruder is moving basically at a constant speed, its future position X, or vector Lx, is estimated from the coordinates of point B and the following formula (3): 
   {right arrow over (Lx)}= 2 ·{right arrow over (Lb)}−{right arrow over (La)}   (3)  
 This position vector Lx(x, y) gives a predicted pan angle Ox and a predicted tilt angle λx according to the following two formulas (4a) and ( 4   b ): 
 θ x =tan −1 ( Lx ( y )/ Lx ( x ))  (4a)  λ x =tan −1 ( Lx/h )  (4b)  
 where Lx (x) and Lx (y) are x-axis and y-axis components of vector Lx. 
 
       FIG. 8  shows how two cameras are used in tracking and waiting operations. Suppose now that a predicted position is given from the above-described calculation, and that another camera Cb (waiting camera) is placed such that its view range overlaps with that of the camera Ca (tracking camera). Then the following three formulas (5), (6a), and (6b) will give the distance r, pan angle θ1, and tilt angle θ2 of the waiting camera Cb. 
   r =( L+Lx− 2 ·L·Lx· cos(θ−θ x ))/2  (5)  θ1=cos −1 (( L+r−Lx )/(2 L·r ))  (6a)  θ2=tan −1 ( r/h 2)  (6b)  
 where L, h2, and θ are known from the mounting position of camera Cb, and Lx, λx, and θx are outcomes of the above formulas (4a) and (4b). 
 
      The object location calculator  41  calculates tilt angle θ2 and pan angle θ1 of the waiting camera Cb in the way described above and sends them to the corresponding rotator driver and rotation controller for that camera Cb, thereby directing the camera Cb against the predicted intruder position.  
     Moving Object Discrimination  
      This section describes the process of discriminating moving objects.  FIG. 9  shows the structure of the third image processor  22 - 2  and moving object discriminator  45 . The third image processor  22 - 2  includes a binarizing operator  2   a , a labeling unit  2   b , a histogram calculator  2   c , and a shape recognition processor  2   d . The moving object discriminator  45  includes a human detector  45   a.    
      The binarizing operator  2   a  produces a binary picture from a given infrared image of the infrared camera C 2  by slicing pixel intensities at a predetermined threshold. Every pixel above the threshold is sent to the labeling unit  2   b , where each chunk of adjoining pixels will be recognized as a single group and labeled accordingly. For each labeled group of pixels, the histogram calculator  2   c  produces a histogram that represents the distribution of pixel intensities ( 256  levels). The shape recognition processor  2   d  calculates the length-to-width ratio of each labeled group of pixels. Those image processing result signals (i.e., histograms and length-to-width ratios) are supplied to the human detector  45   a  for the purpose of moving object discrimination. The human detector  45   a  then determines whether each labeled group represents a human body object or any other object.  
       FIG. 10  depicts the length-to-width ratio of a labeled group of pixels. As seen, the shape recognition processor  2   d  measures the vertical length Δy and horizontal length Δx of this pixel group and then calculates the ratio of Δy:Δx. If the object is a human, the shape looks taller than it is wider. If the object is a car, the shape looks wider and has a large number of pixels. The range of length-to-width ratios for each kind of moving objects is defined previously, allowing the moving object discriminator  45  to differentiate between moving objects by comparing their measured length-to-width ratios with those set values.  
     Movement Path Analysis  
      This section describes the first and second movement path analyzers  42   a  and  42   b  (collectively referred to as movement path analyzers  42 ).  FIG. 11  shows a movement path map m. The movement path analyzer  42  creates such a movement path map m on a two-dimensional coordinate plane to represent the scanning range, or coverage area, of a camera. The movement path map m is divided into a plurality of small blocks, and the movement path analyzer  42  records given movement paths of ordinary moving objects on those blocks. Note that the term “ordinary moving objects” refers to a class of moving objects that are not the subject of surveillance, which include, for example, ordinary men and women and vehicles moving up and down the road. Blocks containing frequent movement paths are designated as mask blocks according to operator instructions. The movement path analyzer  42  regards the objects in such mask blocks as ordinary moving objects.  
      When the camera detects an object, the movement path analyzer  42  calculates its coordinates from the current tilt and pan angles of the camera and determines whether the calculated coordinate point is within the mask blocks on the movement path map m. If it is, the movement path analyzer  42  regards the object in question as an ordinary moving object, thus sending a tracking cancel signal to avoid unnecessary tracking. If not, the movement path analyzer  42  permits the corresponding image processor to keep tracking the object.  
     Variation of Surveillance System  
      This section presents a variation of the surveillance system  1   a , with reference to its block diagram shown in  FIG. 12 . In addition to the components shown in FIGS.  3  to  5 , this surveillance system  1   b  has another set of video surveillance functions including: a visible-light integrating camera C 3 , an infrared camera C 4 , rotators  31   a  and  32   a , tracking controllers  10   a  and  20   a , and a system controller  40   a.    
      Suppose that an intruder comes into the range of the first visible-light integrating camera C 1 . As described earlier in FIGS.  3  to  5 , this event causes the corresponding object location calculator in the first system controller  40  to receive an intrusion alarm and rotation parameters, thus starting to keep track of the intruder. Rotation parameters indicating the predicted object position are sent to the rotation controller of the first infrared camera C 2 , so that the camera C 2  will turn toward the intruder.  
      In the surveillance system  1   b , the same rotation parameters are also sent to the system coordinator  52  via the network  200  and network interface  51 . Since the mounting position of the second visible-light integrating camera C 3  is known, the system coordinator  52  can calculate the tilt and pan angles of the camera C 3  so as to rotate it toward the predicted intruder position. Those parameters are delivered to the corresponding rotation controller (not shown) in the second system controller  40   a  through the network interface  51  and network  200 , thus enabling the second visible-light integrating camera C 3  to wait for the intruder to come into its view range. The same control technique applies to the first and second infrared cameras C 2  and C 4 . In this way, the surveillance system  1   b  keeps observing the intruder without interruption.  
     Conclusion  
      To summarize the above discussion, the proposed surveillance system has a visible-light integrating camera C 1  and an infrared camera C 2  and consults a sunlight table T to determine which camera to use. In daytime hours, the visible-light integrating camera C 1  keeps track of a moving object, while the infrared camera C 2  waits for a moving object to come into its view range. In nighttime hours, on the other hand, the infrared camera C 2  keeps track of a moving object, while the visible-light integrating camera C 1  waits for a moving object to come into its view range. This structural arrangement enables the system to offer 24-hour surveillance service in more accurate and efficient manner. The use of a visible-light integrating camera C 1  eliminates the need for floodlights, thus making it possible to follow the intruder without his/her knowledge.  
      The proposed system further provides a function of determining whether an observed moving object is a subject of surveillance. If it is, the system continues tracking that object. Otherwise, the system cancels further tracking tasks for that object.  
      The system also defines mask blocks by analyzing movement paths of objects. Objects found in mask blocks are disregarded as being ordinary moving objects out of the scope of surveillance. This feature avoids unnecessary tracking, thus increasing the efficiency of surveillance.  
      The foregoing is considered as illustrative only of the principles of the present 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 construction and applications shown and described, and accordingly, all suitable modifications and equivalents may be regarded as falling within the scope of the invention in the appended claims and their equivalents.