Detection and Tracking of Moving Objects

Abstract

Techniques for performing visual surveillance of one or more moving objects are provided. The techniques include registering one or more images captured by one or more cameras, wherein registering the one or more images comprises region-based registration of the one or more images in two or more adjacent frames, performing motion segmentation of the one or more images to detect one or more moving objects and one or more background regions in the one or more images, and tracking the one or more moving objects to facilitate visual surveillance of the one or more moving objects.

1 . A method for performing visual surveillance of one or more moving objects, wherein the method comprises:
 registering one or more images captured by one or more cameras, wherein registering the one or more images comprises region-based registration of the one or more images in two or more adjacent frames;   performing motion segmentation of the one or more images to detect one or more moving objects and one or more background regions in the one or more images; and   tracking the one or more moving objects to facilitate visual surveillance of the one or more moving objects.   
     
     
         2 . The method of  claim 1 , wherein registering one or more images comprises recursive global and local geometric registration of the one or more images. 
     
     
         3 . The method of  claim 1 , wherein registering one or more images comprises using one or more sub-pixel image matching techniques. 
     
     
         4 . The method of  claim 1 , wherein performing motion segmentation of the one or more images comprises forward and backward frame differencing. 
     
     
         5 . The method of  claim 4 , wherein forward and backward frame differences comprises automatic dynamic threshold estimation based on at least one of temporary filtering and spatial filtering. 
     
     
         6 . The method of  claim 4 , wherein forward and backward frame differences comprises removing one or more false moving pixels based on independent motions of one or more image features. 
     
     
         7 . The method of  claim 4 , wherein forward and backward frame differences comprises performing a morphological operation and generating one or more motion pixels. 
     
     
         8 . The method of  claim 1 , wherein tracking the one or more moving objects comprises performing hybrid target tracking, wherein hybrid target tracking comprises using a Kanade-Lucas-Tomasi feature tracker and meanshift, using auto kernel scale estimation and updating, and using one or more feature trajectories. 
     
     
         9 . The method of  claim 1 , wherein tracking the one or more moving objects comprises using one or more multi-target tracking algorithms based on feature matching and distance matrices for one or more targets. 
     
     
         10 . The method of  claim 1 , wherein tracking the one or more moving objects comprises:
 generating a motion map;   identifying one or more moving objects;   performing object initialization and object checking;   identifying one or more object regions in the motion map;   extracting one or more features;   setting a search region in the motion map;   identifying one or more candidate regions in the motion map;   meanshift tracking;   identifying one or more moving objects in the one or more candidate regions;   performing Kanade-Lucas-Tomasi feature matching;   performing an affine transform;   making a final regions determination via the Bhattacharyya coefficient; and   updating a target model and trajectory information.   
     
     
         11 . The method of  claim 1 , wherein tracking the one or more moving objects comprises reference plane-based registration and tracking. 
     
     
         12 . The method of  claim 1 , further comprising relating each camera view with one or more other camera views. 
     
     
         13 . The method of  claim 1 , further comprising forming a panoramic view from the one or more images captured by one or more cameras. 
     
     
         14 . The method of  claim 13 , further comprising estimating motion of each camera based on video information of one or more static objects in the panoramic view. 
     
     
         15 . The method of  claim 13 , further comprising estimating one or more background structures in the panoramic view based on linear structure detection and statistical analysis of the one or more moving objects over a period of time. 
     
     
         16 . The method of  claim 1 , further comprising automatic feature extraction, wherein automatic feature extraction comprises:
 framing an image;   performing a Gaussian smoothing operation;   using a canny detector to extract one or more feature edges;   implementing a hough transformation for feature analysis;   determining a maximum response finding for reducing an influence of multiple peaks in a transform space;   determining if a length of a feature is greater than a certain threshold, and if the length of the feature is greater than the threshold, performing feature extraction and pixel removal.   
     
     
         17 . The method of  claim 16 , wherein automatic feature extraction further comprises performing frame differencing and verification via motion history images. 
     
     
         18 . The method of  claim 1 , further comprising performing outlier removal to remove one or more incorrect moving object matches. 
     
     
         19 . The method of  claim 1 , further comprising false blob filtering, wherein false blob filtering comprises:
 generating a motion map;   applying a connected component process to link each blob data;   creating a motion blob table;   extracting one or more features for each blob in a previously registered frame; and   applying a Kanade-Lucas-Tomasi method to estimate motion of each blob, and, if no motion occurs for a blob, deleting the blob from the blob table.   
     
     
         20 . The method of  claim 1 , further comprising updating a target model on at least one of a temporal domain and a spatial domain. 
     
     
         21 . The method of  claim 1 , further comprising creating an index of object appearances and object tracks in a panoramic view. 
     
     
         22 . The method of  claim 21 , further comprising determining a similarity metric between a query and an entry in the index. 
     
     
         23 . The method of  claim 1 , further comprising providing a system, wherein the system comprises one or more distinct software modules, each of the one or more distinct software modules being embodied on a tangible computer-readable recordable storage medium, and wherein the one or more distinct software modules comprise a geometric registration module, a motion extraction module and an object tracking module executing on a hardware processor.