Abstract:
A video retrieval system is proposed that retrieves trajectory data from a database as a response to a search query. The search query is formulated on the basis of a search trajectory, which is represented as a plurality of search segments. Minimum hounding areas are generated, whereby the plurality of the minimum hounding areas cover the search trajectory or at least one of the search segments. The video retrieval system accesses the database by using at least one of the minimum bounding areas as a query area, whereby the minimum bounding areas of the plurality of bounding areas are arranged overlap-free and/or adjacently or with a search trajectory independent overlap.

Description:
CROSS-REFERENCE 
     The invention described and claimed hereinbelow is also described in PCT/EP2006/060300, filed on Feb. 27, 2006. This patent application, whose subject matter is incorporated here by reference, provides the basis for a claim of priority of invention under 35 U.S.C. 119 (a)-(d). 
     BACKGROUND OF THE INVENTION 
     The invention relates to a video retrieval system for retrieving video data. More specifically the invention relates to a video retrieval system with a retrieval means for retrieving trajectory data from a database as a response to a search query, whereby the search query is formulated on the basis of a search trajectory, which is representable and/or represented as a plurality of search segments, whereby the retrieval means comprises interpreting means for generating a plurality of minimum bounding areas, whereby the plurality of the minimum bounding areas covers the search trajectory or at least one of the search segments and whereby the retrieval means is realised for accessing the database by using at least one of the minimum bounding areas as a query area. Further the invention relates to a respective method and a computer program. 
     Nowadays, video cameras are often used for monitoring areas under surveillance. For monitoring more complex surroundings a plurality of video cameras are commonly employed, whereby the resulting data from the plurality of video cameras is viewed on-line or stored in data-bases and checked off-line. With a growing number of video cameras also the amount of the stored video data is increasing rapidly, which finally results in an enormous effort to search through the video data on- or off-line in case a time instance or location of a certain interesting event is unknown. Improvements are achieved by using systems for content-based indexing and retrieval of video data. 
     In the field of moving-objects-tracking it is known to use video content analysis algorithms (VCA) in order to support the search and the retrieval of video data, whereby in a first step the video camera images are segmented into static background and moving objects. In a further step these objects are tracked over time and the locations of the objects in each frame are extracted. The set of locations of each object over the life-time of the object is converted into a trajectory for each object. These trajectories can be stored in a database and used to search through the recorded video camera images. 
     The document U.S. Pat. No. 6,587,574 B1 discloses a system and a method for representing trajectories of moving objects for content-based indexing and retrieval of visually animated data. The method comprises the steps as elucidated above, whereby a descriptive data structure is generated on the basis of the extracted trajectories and whereby the descriptive data structure comprises at least trajectory data representative for the position, velocity and/or acceleration of the moving object. 
     A solution for an effective storage and retrieval of the video data is disclosed in the scientific article from A. Albers, R. Wijnhoven, E. Jaspers and P. d. With, Smart Search &amp; Retrieval On Video Databases, 2006, Digest of Technical Papers, IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, Nev., USA, January, 2006, which appears to be the closest state of the art. The authors propose in this article to use a hierarchical structure in the form of a so-called Re*-tree for indexing the video data, which is based on the idea of indexing the trajectories of moving objects by dividing the trajectories into segments, which are allocated to so-called minimum bounding rectangles. In order to optimize the data-structure, the authors propose to apply a spatial filtering on the trajectories prior to allocating the segments to the minimum bounding rectangles. 
     SUMMARY OF THE INVENTION 
     The video retrieval system and/or apparatus is preferably realised for retrieving video data, especially video sequences, images etc. For that purpose the video retrieval system provides retrieval means which is adapted and/or realised to retrieve trajectory data from a database, whereby the database is preferably part of the video retrieval system. The trajectory data is retrieved as a response to a search query, whereby the search query is formulated on the basis of a search trajectory, which (i.e. the search trajectory) is representable and/or represented as a plurality of search segments. The search trajectory is preferably expressed as a spatial trajectory and/or in spatial representation. In preferred embodiments the search trajectory is a line and/or the search segments are realised as line segments. Preferably, the retrieved trajectory data is linked to and/or pointing at the video data and/or the video sequences corresponding to the retrieved trajectory data, so that the video data and/or the video sequences corresponding to the retrieved trajectory data can be retrieved. Trajectory data is preferably defined as data comprising trajectory information of the moving object, whereby the information includes for example information representative for a position, a velocity and/or an acceleration of the moving object. 
     The retrieval means comprises interpreting means for generating a plurality of minimum bounding areas, whereby in a spatial representation the plurality of the minimum bounding areas covers the search trajectory or at least one of the search segments. In the first alternative, the plurality of minimum bounding areas covers the complete search trajectory, in the latter alternative, the plurality of minimum bounding areas covers especially one or two and/or more search segments. The covering is preferably realised so that the plurality of the minimum bounding areas in their entirety covers an area in which the search trajectory and/or at least one search segment is lying. 
     Furthermore the retrieval means is realised to access the database by using at least one of the minimum bounding areas as a query area. Preferably the retrieval means is programmed and/or wired and/or comprises a circuit to provide the above-identified features. The minimum bounding areas are used as sub-queries, whereby the database returns trajectory data of trajectories and whereby the trajectories preferably are indexed by indexing bounding areas overlapping with the respective query area and/or comprise interpolating points lying inside the query area. 
     According to the invention the minimum bounding areas of the plurality of bounding areas are arranged overlap-free and/or adjacently or with a search trajectory independent overlap. The search trajectory-independent overlap is preferably pre-defined for example as a system parameter and/or is dependent from the distance of single location and/or interpolating points of the trajectories stored in the database. 
     The underlying idea and the main benefit of the invention is to realize the retrieval means so that the overlap of the minimum bounding areas is minimised. It is most preferred to arrange the areas overlap-free, but for technical reasons in some applications an overlap concerning the borderlines and/or an overlap in general is necessary to improve the programming of the respective algorithm As preferably each minimum bounding area is used as a sub-query, the overall overlap between the plurality of the minimum bounding areas on the one hand side and indexing bounding areas on the other side is minimized and thus the number of double results and consequently the search time is decreased. 
     Preferably means are provided for formulating different kinds of search queries, which preferably allow an intuitive search. Non-restricting embodiments are: Area-of-interest query in order to retrieve trajectory data about moving objects passing through, entering and/or leaving a selected area of interest and/or having a trajectory overlapping with the area-of-interest. Line-crossing query in order to retrieve trajectory data about moving objects crossing a selected line. Trajectory-by-sketch search in order to retrieve trajectory data about moving objects having a trajectory similar or identical to a sketched trajectory. Trajectory-by-example query in order to retrieve trajectory data of trajectories, which are similar and/or identical to a selected trajectory of a moving object. One-click-trajectory in order to retrieve trajectory data of trajectories which are similar to an example trajectory which is selected by a computer-mouse click or by another typical user input action. The example trajectory is preferably a result trajectory of a prior query. Alternatively an object is selected, the trajectory of the object is retrieved in a first step and in a second step all trajectories similar to the retrieved trajectory of the selected object are retrieved. These or further different kinds of search queries are optionally combinable with further conditions concerning velocity, moving direction, acceleration, colour and/or type of the moving object and/or the like. 
     In a preferred embodiment, the minimum bounding areas and/or the indexing bounding areas are realized as rectangles. In this preferred embodiment, the trajectories in the database are indexed by indexing bounding rectangles, preferably as disclosed in the above-introduced paper from A. Albers, R. Wijnhoven, E. Jaspers and P. d. With, which is incorporated herein by reference in its entirety, especially concerning the sections “data representation” and “database access method”. Also preferred is the use of a hierarchical database structure, especially an R-tree or an R*-tree structure or another hierarchical spatial data structure. The borderlines of the minimum bounding areas and the borderlines of the indexing bounding areas are preferably parallel or perpendicular to each other, so that the possible trajectory independent overlap is also rectangle-shaped. 
     In a further embodiment the video retrieval system comprises segmenting means realised to divide the search trajectory in search segments, which are preferably line segments. Preferably the segmenting means are embodied to divide the search trajectory in linear and/or straight and/or quasi-linear and/or quasi-straight segments. Preferably a plurality of minimum bounding areas is generated for each segment. 
     It is further preferred that the video retrieval system comprises filtering means for spatial filtering the trajectories, especially prior to processing and/or storing the trajectories. The spatial filtering is especially adapted to derive interpolating points from the location points of the trajectories and thus to reduce the number of location points of the trajectory while preferably preserving the directional and/or spatial information. The spatial filtering is for example realised by a low-pass filter and/or by a filter using spatial bounding tubes and/or spatial maximum distance circles as described in the above-introduced paper from A. Albers, R. Wijnhoven, E. Jaspers and P. d. With. The spatial filtering is applied on the trajectories prior to storing in the database and/or on the search trajectory. 
     Further advantages are achievable by an optional embodiment of the invention, wherein the video retrieval system provides ranging means, which is realised for generating a minimum matching range for the single search segment and/or for the search trajectory, whereby the plurality of minimum bounding rectangles are realised to cover the minimum matching range. Preferably the minimum matching range covers the area in a minimum distance from the single search segment and/or from the search trajectory, whereby the minimum distance is preferably defined by the characteristics of the filtering means. In case of a spatial filtering the minimum distance is preferably defined in respect to the maximum or mean distance between two (filtered) interpolating points of the trajectories stored in the database and/or of the search trajectory, especially as half of the maximum distance between two filtered interpolating points. Particularly, the ranging means allows to compensate for negative effects of the filtering means, as the filtering means narrows the spatial extension of the trajectories in the database, thus resulting in a possible loss of matching trajectories. In order to restitute and/or compensate the lost area of the indexing minimum bounding boxes, the ranging means increases artificially the extension of the search trajectory or search segments by generating the minimum matching range. 
     In a very useful optional embodiment the interpreting means are realised to generate an intermediate bounding box for the single search segment and/or search trajectory and to split the intermediate bounding box into the plurality of minimum bounding boxes, whereby preferably one single intermediate bounding box is generated per search segment and/or search trajectory. Preferably the intermediate box is split and optionally partially cancelled, so that the area covered by the generated minimum bounding boxes in their entirety is smaller than the area of the respective intermediate bounding box. The partially cancelling of the intermediate box is preferably achieved by adapting the minimum bounding boxes to the minimum matching range of the respective search segment. Preferably the number of rectangle split-ups is dependent on the length of the respective search segment and/or on the angle between the search segment and the preceding and/or the following search segment of a search trajectory and/or on the angle of the search segment relative to the orientation of the rectangles of the indexing bounding boxes. Further preferably a maximum split-up factor is defined by the distance between the interpolating points of the trajectories stored in the database, whereby the maximum split-up factor satisfies the condition that a minimum diameter of minimum bounding boxes is larger or equal to the minimum distance of the interpolating points. 
     The invention further proposes a video retrieval system according to the preamble of claim  1  and/or to one of claims  1  to  6 , whereby prioritising means realised for allocating a search priority to search objects, like the search trajectories and/or the search segments and/or the minimum bounding areas, are provided, preferably comprising the further features of one or any of the claims  1  to  6 . With the option of allocating priorities the video retrieval system allows, that search trajectories, search segments and/or minimum bounding areas with a higher priority level are processed with a higher system performance than such search objects with a lower priority level and/or are processed prior and/or before such search objects with a lower priority level. 
     In a further embodiment, the prioritising means comprise and/or are connected with input means for setting the priorities manually, especially by a user interaction. Alternatively the prioritising means are realised for setting the priorities automatically, especially dependent on a busyness and/or density table of the search area defined by the search trajectory, search segment or minimum bounding area. Preferably search areas with a higher density of stored trajectories and/or busyness of stored moving objects are allocated to a lower priority level, whereas areas with a lower density are allocated to a higher priority level. The underlying idea is that results from search areas with a lower density and/or busyness allow a faster retrieval of results, so that first results at least concerning the higher prioritised areas are retrieved quickly. 
     Further preferred is that the prioritising means allow a combination of manual and automatic prioritisation, whereby preferably in a first step priorities are set manually and in a second step sub-priorities are set automatically (or vice versa) and/or search segments and/or minimum bounding areas without a manually set priority are allocated to a priority automatically. Further a preferably automatically sub-priorisation is possible. 
     In a very useful embodiment, the video retrieval system is realised for retrieving and/or displaying intermediate results on the basis of results of higher prioritised search segments and/or minimum bounding areas without using results of lower prioritised search segments and/or minimum bounding areas. The intermediate results are trajectories stored in the database and/or trajectory data thereof. This embodiment allows for example that intermediate results concerning a search trajectory with more than two search segments are retrieved and/or displayed when only one or a subset of the search segments are searched in the database, so that preliminary but early feedback is provided for the user. Especially, the video retrieval system is realised to provide intermediate results after each sub-query. 
     The method for retrieving video data according to claim  11  uses preferably a video retrieval system as described above and comprises the steps of: 
     formulating a search query on the basis of a search trajectory, which is representable and/or represented as a plurality of search segments, generating a plurality of minimum bounding areas, whereby the plurality of the minimum bounding areas covers the search trajectory or at least one of the search segments and whereby the minimum bounding areas of the plurality of bounding areas are arranged overlap-free and/or adjacently or with a search trajectory independent overlap and/or allocating search priorities to the search trajectories and/or to the search segments and/or to the minimum bounding areas, accessing a database by using at least one of the minimum bounding areas as a query area within the search query and retrieving trajectory data from the database as a response to the search query. Preferably the retrieved trajectory and/or trajectory data is compared with the search query for evaluating the match quality. 
     Optionally the method comprises the steps of filtering with the filtering means and/or segmenting with the segmenting means and/or splitting up with the interpreting means and/or allocating priorities with the prioritizing means and/or presenting intermediate results with the retrieving and/or displaying means. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of the invention and the advantages thereof reference is made to the following descriptions taken into conjunction with the accompanying drawings, wherein similar numbers designate similar objects. The drawings show: 
         FIG. 1  a schematic overview of a video retrieval system as a first embodiment of the invention; 
         FIG. 2  a schematic overview to illustrate extracting and filtering of trajectories as preferably used in the video retrieval system in  FIG. 1 ; 
         FIG. 3  a schematic overview of the hierarchical storing of the filtered or pre-processed trajectory and of the retrieval thereof, preferably used in the video retrieval system in  FIG. 1 ; 
         FIG. 4  an illustration of a step of generating intermediate minimum bounding boxes, preferably used in the video retrieval system in  FIG. 1 ; 
         FIG. 5  an illustration of a step of splitting up intermediate minimum bounding boxes, preferably used in the video retrieval system in  FIG. 1 ; 
         FIG. 6  an illustration of a step of allocating search priorities to the search segments and/or minimum bounding boxes, preferably used in the video retrieval system in  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       FIG. 1  shows a schematic overview of the general concept of a video retrieval system  1 . On the left hand side of  FIG. 1  object tracking is illustrated by means of an image  2  of a traffic crossing with overlaid trajectories  3   a  and  b  and object detection windows  4   a  and  4   b . In the image  2  two lines are shown representing two trajectories  3   a  and  b  of two different moving objects. The trajectories  3   a  and  b  are extracted from a sequence of video frames, whereby in a first step a segmentation and detection algorithm returned the shape and position of each of the moving objects and in a second step each moving object is tracked over its lifetime in the video sequence So the location points of the moving objects in the video frames are used to form the trajectories  3   a, b , whereby the trajectories  3   a  and  b  are interpolating the centre (or another point) of the object detection windows  4   a  and  4   b  respectively, which are object bounding boxes on a frame-by-frame basis. These trajectories  3   a, b  each being represented by the set of the trajectory-forming location points are filtered and stored in a database  5  as explained later. 
     On the right hand side an image  6  of the traffic crossing is shown, which is similar or identical to the image  2 . In image  6  sketched line-segments  7  are drawn, with one end realised as arrowhead  8 . The sketched line  7  represents a trajectory for a search query in the database  5  for similar trajectories. The arrowhead  8  indicates the moving direction of an object in connection with the search trajectory. 
       FIG. 2  illustrates schematically the extracting and filtering of the trajectory  3   b  as preferably used in the video retrieval system  1  in  FIG. 1 . On the left hand side—again—is the image  2  with the trajectory  3   b , the bounding boxes  4   b  and additionally a set of locations points  9 , each representing the centre of a bounding box  4   b  corresponding to a single frame of the frame sequence. This set of location points  9  is the input for a filtering algorithm as illustrated in the middle of  FIG. 2 . The set of location points  9  is filtered by a spatial correlation algorithm, whereby preferably all location points which are within a predetermined maximum distance defined by a circle  10  around a preceding filtered location point  11  and/or which are within a maximum direction deviation range defined by a tube  12 , which is arranged around the location points  9 , are cancelled. Optionally new points  13  can be created in case no location point  9  of the trajectory  3   b  lies on the circle  10  and the currently considered trajectory point lies outside the circle  10 , and/or a new point can be created on the edge of tube  12  in case the currently considered trajectory point lies outside the tube  12 . The output of the filtering algorithm is represented on the left side of  FIG. 2  showing a smaller set of interpolating points  11 ,  13 ,  14  representing the trajectory  3   b.    
       FIG. 3  illustrates the hierarchical storage of the filtered trajectory data in the database  5  and the database access method. 
     In the upper left corner of  FIG. 3  the filtered trajectories  3   b  and  a  with filtered location points or interpolating points  11 ,  13 ,  14  and  15  respectively are shown. Each trajectory  3   a  and  b  is represented by a first minimum bounding rectangle A, which only contains the information about the outer limit and the position of the complete filtered trajectories  3   a  and  b . In a further step the filtered trajectories  3   a, b  are split up into sub-trails which are represented by minimum bounding rectangles B, C and D respectively, whereby preferably the rectangles B,C and D are arranged within the rectangle A without overlap. The rectangles B, C, D carry the information about the outer limit and the position of the respective sub-trails arranged therein. 
     In the lower part of  FIG. 3  a tree-like data structure  16  is shown, for example an R*-tree. The data structure  16  is indexed by the rectangles A, B, C and D and carries and/or is linked with the information about the trajectories  3   a, b  and sub-trails. The small circles of the tree are called children of the tree and represent the actual stored trajectory points. So summarized the interpolating points of the filtered trajectories  3   a  and  3   b  and further trajectories are distributed between the lowest level of the hierarchical structure, whereby the lowest level is indexed by the minimum bounding rectangles B, C and D. 
     In the upper right corner of  FIG. 3  the database access method in case of a query on the basis of the sketched line-segments  7  concerning a trajectory is demonstrated. First the sketched line-segments  7  are divided in segments  17 ,  18  and  19 . In the following the database access method in connection with the middle line segment  18  is described as an example. In a further step a range window  20  is placed automatically over the middle segment  18  to define a limited matching range. The range window  20  has preferably a curved borderline, whereby the borders of the range window  22  are defined for example by a minimum distance to the trajectory points of the middle query segment  18  and/or to the middle query segment  18  itself. In a subsequent step the range window  20  is converted in an intermediate search minimum bounding rectangle  21 , whereby the borders of the intermediate search minimum bounding rectangle  21  are parallel to the borders of the minimum bounding rectangles A, B, C or D. 
       FIG. 4  illustrates the step of generating intermediate minimum bounding boxes for the remaining line segments  17  and  19  in the same manner as described for the middle segment line  18 , so that finally for each line segment  17 ,  18  and  19  an intermediate minimum bounding box  21 ,  22  and  23  is created. 
     A following step of splitting up the intermediate bounding boxes  21 ,  22  and  23  is illustrated by the  FIG. 5  in connection with the intermediate bounding box  23  as an example. The intermediate bounding box  23  is split up and partially reduced to the minimum bounding boxes  24 ,  25 ,  26  and  27 . Concerning the width these minimum bounding boxes  24 ,  25 ,  26  and  27  are arranged side-by-side within the intermediate minimum bounding box  23  without overlap. Concerning the height the minimum bounding boxes  24 ,  25 ,  26  and  27  are adapted to the diameter of the range window  28  of the segment  19 , so that the plurality of the minimum bounding boxes  24 ,  25 ,  26  and  27  covers the range window  28  completely. The width of the single minimum bounding boxes  24 ,  25 ,  26  and  27  is fixed to a pre-defined size, especially to a defined number of pixels, for example to 20 pixels, in the image  6 . For other line segments and/or embodiments it is possible to arrange a plurality of minimum bounding boxes in the vertical direction side-by-side and adapt the width of the individual minimum bounding boxes. The step of splitting up is performed also for the remaining intermediate bounding boxes  21  and  22  concerning the segments  18  and  17 , respectively. As a result of the splitting up step, the three intermediate minimum bounding boxes  21 ,  22  and  23  are converted into a plurality of minimum bounding boxes  24 ,  25 ,  26 ,  27  and further boxes. It shall be noticed that the intermediate step of generating intermediate bounding boxes  21 ,  22  and  23  is not strictly necessary, as the minimum bounding boxes  24 ,  25 ,  26 ,  27  and further boxes can also be generated by another algorithm. 
     In a first retrieval step the minimum bounding boxes  24 ,  25 ,  26 ,  27  and the further boxes are used as sub-queries and are sent to the database  5 , whereby the search for similar trajectories or parts thereof is only performed in the rectangles of the tree-like data structure  16  overlaying with the minimum bounding boxes  24 ,  25 ,  26 ,  27  and further boxes, respectively. So—as an example—the minimum bounding box  26 , only overlaps with the rectangle B, so trajectory data concerning the rectangles C and D is not accessed. The results of the sub-queries are combined in order to find matching trajectories and/or sub-trails for any or all of the segments  17 ,  18  and  19  of the sketched line-segments  7 . Finally as a result a list of similar trajectories preferably in best-match order is returned. 
     From the foregoing it should be clear that an increase of the area covered by the minimum bounding boxes  24 ,  25 ,  26 ,  27  and the further boxes leads to an increase of the overlap area of the minimum bounding boxes  24 ,  25 ,  26 ,  27  and further boxes in their entirety with the indexing minimum bounding rectangles A, B, C and D, whereby the increase of overlap leads to an increase of data returned by the database  5 . So splitting up and reducing the intermediate bounding boxes finally leads to a decrease of overlap and thus to a decrease of data returned by the database  5 . 
       FIG. 6  illustrates the optional step of setting priorities for the minimum bounding areas  24 ,  25 ,  26  and  27 . It shall be noted that this step can also be used in case no step of splitting up is performed and the intermediate bounding boxes  21 ,  22  and  23  are used as minimum bounding boxes in connection with the sub-queries. 
     On the left hand side the same illustration of the image  6  as in  FIG. 1  is shown with the same sketched line-segments  7 . In this embodiment the user is additionally allowed to allocate priorities to the segments  17 ,  18  and  19  of the line-segments  7 . As an example in  FIG. 6  the user sets the segment  17  to a user priority  2 , indicated by UP 2 , segment  18  to a user priority  1  (UP 1 ) and segment  19  to a user priority  3  (UP 3 ). 
     In the middle part of  FIG. 6 , the priorities for the segments  17 ,  18  and  19  are set by the video retrieval system  1  automatically, indicated by the arrows allocating the priorities P 1  (priority  1 ) to the segment  17 , P 2  (priority  2 ) to the segment  18  and P 3  (priority  3 ) to the segment  19 . Further a combination of manually and automatically allocated priorities is possible. On the right hand side of  FIG. 6  a step of sub-prioritising is illustrated, whereby sub-priorities P 3 . 2 , P 3 . 4 , P 3 . 3 , P 3 . 1  are allocated to the minimum bounding boxes  24 ,  25 ,  26  and  27 , whereby in this example the leading numeral (i.e. “3”) is allocated manually or automatically as already explained and the second numeral (i.e. “0.2”, “0.4”, “0.3”, “0.1”) is generated as a sub-priority, preferably automatically. In operation the video retrieval system  1  performs the sub-queries in the order or sequence of the allocated priorities, so that—for example—first all sub-queries concerning minimum bounding boxes with a priority of 1 are processed, then—after retrieving the intermediate results of these sub-queries—sub-queries with the priority of 2 are launched. The priorities are preferably distributed, so that first areas with a low density and/or low busyness of moving objects are searched and thus only branches in the database with a low number of entries have to be accessed and/or first strategic relevant areas, like entry or exit or crossing areas are searched. The results of the high prioritised sub-queries are collected and used to produce fast intermediate results for the user.