Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Tracking Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hyperplane Approximation for Template Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Coarse-to-Fine Deformable Contour Optimization Framework
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Layered Motion Segmentation and Depth Ordering by Tracking Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Modeling of Dynamic Scenes for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Coupled Parametric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Camouflaged Objects with Weighted Region Consolidation
DICTA '05 Proceedings of the Digital Image Computing on Techniques and Applications
Probabilistic tracking in joint feature-spatial spaces
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
An object tracking scheme based on local density
MMM'07 Proceedings of the 13th international conference on Multimedia Modeling - Volume Part I
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We propose a dominant-feature based matching method for capturing a target in a video sequence through the dynamic decomposition of the target template. The target template is segmented via intensity bands to better distinguish itself from the local background. Dominant feature elements are extracted from such segments to measure the matching degree of a candidate target via a sum of similarity probabilities. In addition, spatial filtering and contour adaptation are applied to further refine the object location and shape. The implementation of the proposed method has shown its effectiveness in capturing the target in a moving background and with non-rigid object motion.