Abstract:
A method and apparatus for performing surveillance comprising: imaging, at a first frame rate, an area ( 4 ) to produce images; detecting, using the images, a feature of interest ( 22 ) within the area ( 4 ); determining a region of interest ( 24 ), the region of interest ( 24 ) corresponding to a region within the area ( 4 ) in which the feature of interest ( 22 ) will be located at a later time-step; and, at the later time-step, using the region of interest ( 24 ), imaging the area ( 4 ) such that images of the region within the area ( 4 ) in which the feature of interest ( 22 ) is located are produced at a second frame rate, while images of the rest of the area ( 4 ) are produced at a third frame rate, the second rate being different to the third rate.

Description:
FIELD OF THE INVENTION 
     The present invention relates to methods and apparatus for performing surveillance. 
     BACKGROUND 
     Aircraft, e.g. Unmanned Air Vehicles (UAVs), are commonly used in surveillance operations. 
     For surveillance operations in which images of an area under surveillance are captured by a UAV and are transmitted from the UAV for use by a remote entity, or stored on the UAV, communication and memory/storage bandwidth requirements tend to be relatively high. This is particularly the case when those images are captured at a high frame rate (i.e. frequency) or with high resolution. 
     These relatively high bandwidth requirements may limit operation of the UAV. 
     SUMMARY OF THE INVENTION 
     In a first aspect, the present invention provides a surveillance process comprising imaging an area under surveillance to produce a plurality of images of the area under surveillance, the images being produced at a first frame rate, detecting, using one or more of the images, a feature of interest within the area under surveillance, determining a region of interest, the region of interest being either a region within the area under surveillance in which the feature of interest will be located at a later time-step, or a region within an image of the area under surveillance corresponding to a region within the area under surveillance in which the feature of interest will be located at a later time-step, and, at the later time-step, using the determined region of interest, imaging the area under surveillance such that images of the region within the area under surveillance in which the feature of interest is located are produced at a second frame rate, whilst images of the area under surveillance not within the region of the area under surveillance in which the feature of interest is located are produced at a third frame rate, the second rate being different to the third rate. 
     The second rate may be a higher rate than the third rate. 
     The first rate may be substantially equal to the third rate. 
     The surveillance process may further comprise performing a tracking process to track the detected feature of interest or to track the determined region of interest over a period of time. 
     The tracking process may be performed automatically by one or more processors. 
     The step of detecting may be performed automatically by one or more processors. 
     The step of detecting may be performed manually by an operator (e.g. a human operator). 
     The step of detecting the feature of interest may comprise performing a change detection algorithm to detect a change between one of the generated images and a subsequently generated image. 
     At the later time-step, the images of the region within the area under surveillance in which the feature of interest is located may have a first resolution, whilst the images of the area under surveillance not within the region of the area under surveillance in which the feature of interest is located may have a second resolution. 
     The first resolution may be higher than the second resolution. 
     The imaging may be performed using sensor array comprising a plurality of sensors. A rate at which each sensor in the sensor array captures images may be changed independently from that of each of the other sensors. 
     The sensor array may be a Complementary Metal Oxide Semiconductor sensor. 
     In a further aspect, the present invention provides surveillance apparatus comprising one or more sensors configured to image an area under surveillance to produce a plurality of images of the area under surveillance, the images being produced at a first frame rate, and one or more processors operatively coupled to the one or more sensors and configured to detect, using one or more of the images, a feature of interest within the area under surveillance, and determine a region of interest, the region of interest being either a region within the area under surveillance in which the feature of interest will be located at a later time-step, or a region within an image of the area under surveillance corresponding to a region within the area under surveillance in which the feature of interest will be located at a later time-step, wherein the one or more sensors are further configured to, at the later time-step, imaging the area under surveillance such that images of the region within the area under surveillance in which the feature of interest is located are produced at a second frame rate, whilst images of the area under surveillance not within the region of the area under surveillance in which the feature of interest is located are produced at a third frame rate, the second rate being different to the third rate. 
     In a further aspect, the present invention provides an aircraft comprising surveillance apparatus according to the previous aspect. 
     The surveillance apparatus may further comprise a transmitter operatively coupled to the one or more sensors and configured to transmit, for use by an entity remote from the aircraft, the images produced at the later time-step. 
     In a further aspect, the present invention provides a program or plurality of programs arranged such that when executed by a computer system or one or more processors it/they cause the computer system or the one or more processors to operate in accordance with the method of any of the above aspects. 
     In a further aspect, the present invention provides a machine readable storage medium storing a program or at least one of the plurality of programs according to the previous aspect. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a schematic illustration (not to scale) of an example scenario; 
         FIG. 2  is a schematic illustration (not to scale) of an unmanned air vehicle; 
         FIG. 3  is a process flow chart showing certain steps of an embodiment of a surveillance process; and 
         FIG. 4  is a schematic illustration (not to scale) of an example image. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  is a schematic illustration (not to scale) of a scenario  1  in which an unmanned air vehicle (UAV)  2  is used to perform an embodiment of a surveillance process. The surveillance process is described in more detail later below with reference to  FIG. 3 . 
     In this scenario  1 , the UAV  2  files over (or proximate to) an area of terrain  4 . As UAV  2  flies over the area of terrain  4 , the UAV  2  performs surveillance of the area of terrain  4  (and the building  6  therein). This surveillance comprises the UAV  2  capturing images of the area of terrain  4  as described in more detail later below with reference to  FIG. 4 . 
     In this scenario  1 , the area of terrain is outdoors. However, in other scenarios, a different type of area is under surveillance (i.e. the area to be surveilled is an area that is not outdoors). For example, in other embodiments, the area to be surveilled may be within a building. 
     In this scenario  1 , the UAV  2  is connected to a ground station  8  by a wireless data-link  10 . This connection is such that information may be sent between the UAV  2  and the ground station  8 . The UAV  2  may, for example, be controlled by an operator (e.g. a human operator) located at the ground station  8 . 
       FIG. 2  is a schematic illustration (not to scale) of the UAV  2 . 
     The UAV  2  comprises a sensor  12 , a data acquisition module  14 , an automatic change detection (ACD) module  16 , and a transceiver  18 . 
     In this embodiment, the sensor  12  is a conventional Complementary Metal Oxide Semiconductor (CMOS) sensor comprising an array of pixel sensors. Each of the respective pixel sensors of the sensor  12  is configured to capture images of a respective different portion of the area of terrain  4  as the UAV  2  flies over, or proximate to, the area of terrain  4 . This is such that the whole of the area of terrain  4  (and the building  6 ) may be imaged using the sensor  12 . 
     The sensor  12  may be mounted on the UAV  2  via a gimbal (not shown in the Figures). 
     The sensor  12  is connected to the data acquisition module  14  such that information may be sent from the sensor  12  to the data acquisition module  14  and vice versa. 
     In this embodiment, the data acquisition module  14  is configured to provide, or “drive”, a control signal for each of the pixel sensors of the sensor  12 . Also, the data acquisition module  14  is configured to provide, or “drive” a clock signal for each of the pixel sensors of the sensor  12 . Thus, the data acquisition module  14  controls the operation of the pixel sensors of the sensor  12 . For example, the data acquisition module  14  may control the rate at which each pixel sensor of the sensor  12  captures images of the portion of the area of terrain  4  that corresponds to that pixel sensor. 
     In addition to being connected to the sensor  12 , the data acquisition module  14  is connected to the ACD module  16 . This is such that information may be sent from the data acquisition module  14  to the ACD module  16  and vice versa. The data acquisition module  14  is also connected to the transceiver  18 . This is such that information may be sent from the data acquisition module  14  to the transceiver  18  and vice versa. 
     In this embodiment, the ACD module  16  is configured to process image data generated by the sensor  12 , as described in more detail later below with reference to  FIG. 3 . 
     In addition to being connected to the data acquisition module  14 , the ACD module  16  is connected to the transceiver  18 . This is such that information may be sent from the ACD module  16  to the transceiver  18  and vice versa. 
     The transceiver  18  is connected to the ground station  8  via the data-link  10  such that information may be sent from the transceiver  18  to the transceiver ground station  8  and vice versa. 
     Apparatus, including the data acquisition module  14  and ACD module  16 , for implementing the above arrangement, and performing the method steps to be described later below with reference to  FIG. 3 , may be provided by configuring or adapting any suitable apparatus, for example one or more computers or other processing apparatus or processors, and/or providing additional modules. The apparatus may comprise a computer, a network of computers, or one or more processors, for implementing instructions and using data, including instructions and data in the form of a computer program or plurality of computer programs stored in or on a machine readable storage medium such as computer memory, a computer disk, ROM, PROM etc., or any combination of these or other storage media. The apparatus may be wholly on-board the UAV  2 , wholly off-board the UAV  2  (e.g. at the ground station  8 ), or partially on board and partially off-board the UAV  2 . 
       FIG. 3  is a process flow chart showing certain steps of an embodiment of a surveillance process performed by the UAV  2  in the above described scenario  1 . 
     At step s 2 , as the UAV  2  flies proximate to the area of terrain  4 , the sensor  12  images the area of terrain  4 , i.e. the sensor  12  captures a sequence of images (i.e. frames) of the area of terrain  4  and the building  6  therein. In particular, each pixel sensor of the sensor  12  captures images of a respective portion of the area of terrain  4 . This is performed such that all of the area of terrain  4  (and building  6 ) is imaged. 
     In this embodiment, at step s 2 , the images are captured over a series of time-steps (i.e. over a time-period). 
     In this embodiment, the images captured by the sensor  12  at step s 2  are captured at a relatively low frame rate, i.e. a relatively low frequency. In other words, at step s 2 , the data acquisition module  14  controls the pixel sensors of the sensor  12  to capture images at a relative low rate, i.e. the control signals for the pixel sensor provided to the sensor by the data acquisition module  14  specify a low frame rate for the pixel sensors. 
     At step s 4 , the image data captured by the sensor  12  is sent from the sensor  12  to the data acquisition module  14 . This may, for example, be performed continuously as the sensor  12  captures images of the area of terrain  4  over a period of time. 
     At step s 5 , the data acquisition module  14  assembles images of the area of terrain  4  from the images taken by the pixel sensors of the sensor  12 . In this embodiment, a sequence of images of the area of terrain  4  is produced. 
     At step s 6 , the assembled images are sent from the data acquisition module  14  to the ACD module  16 . This may, for example, be performed continuously as the data acquisition module  14  assembles the images in the image sequence. 
     At step s 8 , the ACD module  16  performs a change detection algorithm on the received image data. The change detection algorithm is a conventional change detection algorithm for identifying significant changes between a frame and one or more subsequent frames e.g. between one image from the captured sequence of images and a subsequent image. The change detection algorithm may be used to detect objects (e.g. vehicles, people etc.) moving within the area of terrain  4 . 
     Any appropriate change detection algorithm may be used. For example, a change detection algorithm that detects changes based on changes in image contrast or edge detection may be used. In other embodiments, instead of or in addition to the change detection process, a process for detecting anomalous features or behaviour may be used to detect objects. 
     In this embodiment, the change detection algorithm comprises defining one or more “regions of interest” in one or more of the captured images. A region of interest is a region within an image in which the detected change occurs (i.e. in which an object is detected). A region of interest may be defined for each of the detected changes/objects. 
     At step s 10 , the ACD module  16  performs a conventional tracking algorithm. The tracking algorithm is a conventional tracking algorithm for tracking, between frames, the detected objects or image features. 
     In this embodiment, the tracking algorithm may be used to determine a position for a detected object at a next time-step (i.e. at the next time at which an image of the area of terrain  4  is to be captured by the sensor  12 ). The tracking algorithm may also determine a region of interest for the next time step (i.e. a region within an image taken at the next time-step in which the object will most likely be located). Any appropriate tracking algorithm may be used. The size of a region of interest for an object may be dependent upon how certain, or how confident, the tracking algorithm is about the position of that object at the next time step. Also, the size of a region of interest for an object may be dependent upon how quickly that object is moving. For example, the region of interest for an object may be relatively large if that object is a fast moving object compared to if that object was moving more slowly. 
       FIG. 4  is a schematic illustration (not to scale) of an example frame  20  (i.e. image in the captured sequence of images). The frame  20  is an image that contains the area of terrain  4  and the building  6 . The frame  20  further comprises images of objects  22  that are moving within the area of terrain  4 . Regions of interest  24  are defined in the frame  20 . Each region of interest  24  wholly contains an object  22 . Also, the objects  22  have been tracked (as described above with reference to step s 10  of the process of  FIG. 3 ) through the sequence of images along respective paths (indicated in  FIG. 4  by dotted lines and the reference numeral  26 ). 
     At step s 12 , information that identifies the determined positions, at the next time-step, of each region of interest  24  is sent from the ACD module  16  to the data acquisition module  14 . This information may, for example, be coordinates for each of the region of interest  24  (e.g. coordinates of the four corners of a square region of interest) at the time-step. 
     At step s 14 , using the received information, the data acquisition module  14  identifies those pixel sensors of the sensor  12  that, at the time-step, would capture an image within a region of interest  24 . This may be performed in any appropriate way, for example, the data acquisition module  14  may identify pixel sites (i.e. in effect “addresses”) for those pixels that, at the time-step, would capture an image within a region of interest  24 . 
     At step s 16 , the data acquisition module  14  controls the pixel sensors identified at step s 14  (i.e. the pixel sensors that, at the next time-step, are to capture an image with a region of interest  24 ) such that, at the next time-step, those pixel sensors capture images at a relatively high frame rate (compared to the relatively low frame rate with which images are captured at step s 2 ). In this embodiment, the pixel sensors other than those identified at step s 14 , i.e. the pixels sensors that, at the next time-step, are to capture an image that is not in a region of interest  24 , are controlled so as to capture images at the relatively low frame rate. 
     At step s 18 , at the next time-step, the sensor  12  images the area of terrain  4 . The pixel sensors of the sensor  12  that capture an image with a region of interest  24  capture images at a relatively high frequency (i.e. at a relatively high rate), whilst the pixel sensors that generate image pixels not within a region of interest  24  capture images with a relatively low frequency. 
     At step s 20 , the image data captured by the sensor  12  at step s 18  is sent from the sensor  12  to the data acquisition module  14 . 
     At step s 22 , the data acquisition module  14  assembles images from the received image data. Images of the whole of the area of terrain may be produced. Also, a sequence of images of each of the regions of interest  24  may be produced. 
     At step s 24 , the assembled images are sent from the data acquisition module  14  to both the transceiver  18  and the ACD module  16 . 
     In other embodiments, the assembled images may be stored e.g. by the data acquisition module  14 , in a database. This database may be onboard the UAV  2 . The images stored on such a database may be retrieved (e.g. at a later time) from that database e.g. for use by the ACD module  16 , or for sending to the ground station  8  by the transceiver  18 . 
     After step s 24 , the method proceeds to steps s 26  and s 30 . Step s 30  will be described in more detail later below after the description of steps s 26  and s 28 . 
     At step s 26 , the images received by the transceiver  18  are sent from the UAV  2  to the ground station  8  via the data-link  10 . 
     At step s 28 , the images received by the ground station are analysed. This may, for example, be performed by displaying the received imagery to a human operator located at the ground station, and that human operator manually analysing the displayed images. The images may be displayed to the human operator as video footage of the area of terrain  4 . The human operator may manipulate the video footage, or any of the individual images, in any appropriate way (e.g. by zooming, pausing, replaying, fast-forwarding, rewinding etc.). 
     Advantageously, the objects, features and events that are typically deemed to be of interest during surveillance operations, e.g. objects  22  moving within the area of terrain  4 , are provided to the ground station  8  (for analysis) at a higher rate than things not typically of interest. Thus, the regions of interest  24  (that include the objects  22  moving through the area of terrain  4 ) may be displayed to a human operator at the ground station  8  at a relatively high rate. This tends to reduce motion blur and flicker in the portions of the video footage deemed to be of interest. This tends to make analysis of events of interest easier. Also, this tends to increase information content about target motion and tends to increase the chance of capturing information about the target. Also, this tends to make it easier for a human operator to see and track fast moving objects. Furthermore, as regions that are deemed not to be of interest are provided to the ground station at relatively lower rate, the communication bandwidth required for sending images between the UAV  2  and the ground station  8  tends to be reduced compared to if whole images were sent at the relatively higher rate. 
     At step s 30 , the ACD module  16  may determine whether or not the surveillance of the area of terrain  4  is to continue, i.e. whether or not the surveillance operation being performed is to be stopped. The ACD module  16  may determine that the surveillance operation is to be stopped in any appropriate way, for example, the ground station  8  may instruct the UAV  2  to stop the surveillance operation. 
     If, at step s 30 , it is determined that the surveillance of the area of terrain  4  is to continue, the process of  FIG. 3  proceeds back to step s 8 . Thus, the ACD module performs the change detection and tracking processes using the images assembled by the data acquisition module  14  at step s 22 . The detected objects  22  may continue to be tracked, and images of regions of interest  24  surrounding those tracked objects  22  may continue to be captured by the sensor  12  at a relatively high rate. 
     However, if, at step s 30 , it is determined that the surveillance of the area of terrain  4  is not to continue, the process of  FIG. 3  ends. 
     Thus, a surveillance process performed by the UAV  2  is provided. 
     An advantage provided by the above described system and method is that of a reduction in communication bandwidth requirements compared with that of a conventional system. Furthermore, if images are stored e.g. on the UAV, memory/storage requirements tend also to be reduced compared to conventional systems. This reduction in communication bandwidth (and/or memory) tends to be facilitated by transmitting (and/or storing) portions of images that do not contain objects of interest as low rate data, whilst only sub-images (i.e. not the whole image) that contain objects of interest are transmitted (and/or stored) as high rate data. The communication bandwidth and/or memory/storage requirements may be further reduced by only transmitting and/or storing (as relatively high rate data) the sub-images that contain objects of interest and discarding the portions of the image that do not contain those objects of interest (i.e. by not sending/storing the images captured at the relatively low rate). 
     Only sending sub-images that contain objects of interest at a high rate (as opposed to sending the whole of images at high rate) tends to reduce the amount of processing power required. This, in turn, tends to reduce the amount of power, cooling, and storage required for the processing modules. Thus, the weight and cost of the UAV tend to be reduced. Furthermore, for a given amount of processing power, in the above described system, a larger sensor may be used than in a system that transmits whole images at a relatively high rate. 
     This tracking algorithm used by the ACD module to track a detected object may be performed using the high rate images of only the regions of interest, as opposed to high rate full frame images. This advantageously tends to provide that the data acquisition system used may be simpler and cheaper than a data acquisition system used to perform conventional surveillance methods. This is because the data acquisition system used in the above described method tends only to be required to read out the region of interest mages at the high rate as opposed to full frame data. 
     In the above described methods, events that are typically deemed to be important in surveillance operations (e.g. objects moving through the area being kept under surveillance) are automatically detected and tracked. 
     The above described system and method may advantageously be implemented in different surveillance operations (i.e. surveillance operations different to that described above). For example, the above described method may be used to detect, track, and provide high rate video footage of regions of interest when performing road traffic surveillance, crowd control, crowd monitoring, shipping surveillance, air-traffic control, border control, etc. 
     A further advantage provided by the above described system is that the system is modular. This tends to provide that, if desired, any of the modules (e.g. the sensors, the data acquisition module, or the ACD module) can be updated, repaired, replaced, or changed independently of the other modules of the system. Moreover, the modularity of the system tends to provide that additional sensors can easily be incorporated into the system as required (e.g. depending on the application or any constraints on the system such as spatial constraints imposed by the aircraft). Furthermore, due to its modularity the system is advantageously scalable so that it can be implemented on a variety of platforms. 
     A further advantage provided by the above described system and method is that, by using the array of cameras (as opposed to, for example, a camera mounted on turret) is that video of more than one object of interest can be extracted simultaneously from within the field of view of a single camera. Furthermore, the extracted video of objects of interest from all the cameras in the array may be coupled together such that a capability of ‘videoing’ multiple objects of interest at the same time tends to be advantageously provided. 
     It should be noted that certain of the process steps depicted in the flowchart of  FIG. 3  and described above may be omitted or such process steps may be performed in differing order to that presented above and shown in  FIG. 3 . Furthermore, although all the process steps have, for convenience and ease of understanding, been depicted as discrete temporally-sequential steps, nevertheless some of the process steps may in fact be performed simultaneously or at least overlapping to some extent temporally. 
     In the above embodiments, the surveillance process is implemented in the scenario described above with reference to  FIG. 1 . However in other embodiments, the surveillance process may be implemented in a different scenario, e.g. a scenario comprising a plurality of ground stations, a plurality of UAVs and a plurality of targets to be kept under surveillance. 
     In the above embodiments, the surveillance process was implemented using a UAV. However, in other embodiments, the surveillance process may be performed by one or more different entities, e.g. manned aircraft, land-based or water-based vehicles, surveillance systems on or in buildings, etc. 
     In the above embodiments, image data is transmitted from the UAV to the ground station (for analysis). However, in other embodiments, some or all of the image data may not be transmitted from the UAV. For example, some or all of the image data may be stored on board the UAV until the surveillance operation is finished. Also for example, only high rate image data (i.e. video footage of the regions of interest) may be transmitted or stored by the UAV. 
     In the above embodiments, the sensor is a conventional Complementary Metal Oxide Semiconductor (CMOS) sensor comprising an array of pixel sensors. Such a sensor may detect visible light. However, in other embodiments, a different type of sensor or sensor array may be used. For example, in other embodiments, sensors the detect infrared or ultraviolet light may be used instead of or in addition to a visible light detecting sensor (e.g. the CMOS sensor). 
     In the above embodiments, the change detection and tracking algorithms are performed on-board the UAV by the ACD module. However, in other embodiments, the functionality provided by the ACD module may be provided by a different entity. For example, in other embodiments, a human operator may manually detect changes in the low rate images and define regions of interest within those images that are to be readout at a higher rate. These regions of interest may be tracked automatically (e.g. by the ACD module) or manually (e.g. by the human operator). Such a human operator may be located on-board the aircraft or off-board the aircraft (e.g. at the ground station). In other embodiments, a human operator (or other entity) may review and/or edit the objects and regions of interest generated and tracked by the ACD module. 
     In the above embodiments, the regions of interest determined and tracked by the ACD module (at steps s 8  and s 10  of the process of  FIG. 3 ) are imaged differently to region not of interest (i.e. other regions). In particular, those regions of interest are imaged at a higher rate. However, in other embodiments, those regions of interest may be imaged in a different way to that described above. For example, in other embodiments, the determined and tracked regions of interest may be imaged at a relatively higher resolution than regions not of interest. Relatively lower resolution images of regions that are not of interest may, for example, be gathered by grouping together (or binning) multiple pixel sensors that are to image those regions, and imaging the area of terrain using those groups (whilst relatively higher resolution images of the regions of interest may, for example, be gathered by not grouping together the pixel sensors that are to image the regions of interest, and imaging the regions of interest as described in the above embodiments). In other embodiments, the determined and tracked regions of interest may be imaged at both a relatively higher resolution and a relatively higher rate than regions not of interest.