Shape and motion from image streams under orthography: a factorization method
International Journal of Computer Vision
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion-based segmentation and contour-based classification of video objects
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Image Segmentation for Human Tracking Using Sequential-Image-Based Hierarchical Adaptation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Stochastic Human Segmentation from a Static Camera
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
A Hierarchical Approach to Robust Background Subtraction using Color and Gradient Information
MOTION '02 Proceedings of the Workshop on Motion and Video Computing
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Real-time Human Motion Analysis by Image Skeletonization
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
A study of a target tracking algorithm using global nearest neighbor approach
CompSysTech '03 Proceedings of the 4th international conference conference on Computer systems and technologies: e-Learning
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
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The proposed video surveillance method comprises segmentation of moving targets and tracking the detected objects through five features of the target. We introduce motion object segmentation by fusion of 3-frame temporal differencing and edge-based detection, which is further updated by a median filter. The combination of the five features spatial positions, LBW, Compactness, Orientation and color histogram through particle filter approach tracks the segmented objects. These five features help in matching the target tracks during occlusions, merging of targets, stop and go motion in vary challenging environmental (rainy and snowy) conditions shown in the results. Our proposed method provides solution to common problems related to matching of target tracks. We provide encouraging experimental results calculated on synthetic and real world sequences to demonstrate the algorithm performance.