Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
Edge Flow: A Framework of Boundary Detection and Image Segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Extraction and Analysis of Multiple Periodic Motions in Video Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraint Integration for Efficient Multiview Pose Estimation with Self-Occlusions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Sequential Kernel Density Approximation and Its Application to Real-Time Visual Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation and Tracking of Multiple Humans in Crowded Environments
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coarse-to-Fine Segmentation and Tracking Using Sobolev Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Video Behavior Profiling for Anomaly Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A reliable event-driven strategy for real-time multiple object tracking using static cameras
Advances in Multimedia
Resolving the ambiguity of real-time multiple object tracking using static cameras
International Journal of Intelligent Systems Technologies and Applications
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Object segmentation and tracking are important techniques in video applications. In this paper, we present a novel system for active contour tracking of moving objects in video sequences. Our method includes preprocessing to identify an initial object contour, and object contour segmentation to refine the contour of the moving object. The edge flows and ant colony optimization are incorporated to improve the efficiency during system convergence. Experimental results demonstrated that our system has achieved the automatic segmentation accuracy of