Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
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
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking Deformable Objects in the Plane Using an Active Contour Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
IEEE Transactions on Image Processing
A binary level set model and some applications to Mumford-Shah image segmentation
IEEE Transactions on Image Processing
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Traditional mean shift method has the limitation that could not effectively adjust kernel bandwidth to represent object accurately. To address this problem, in this paper, we propose a novel contour tracking algorithm using a determined binary level set model (DBLSM) based on mean shift procedure. In contrast with other previous work, the computational efficiency is greatly improved due to the simple form of the level set function and the efficient mean shift search. The DBLSM add prior knowledge of the target model to the implementation of curve evolution and ensure a more accurate convergence to the target. Then we use the energy function to measure weight for samples in mean shift framework. Experiment results on several challenging video sequences have verified the proposed algorithm is efficient and effective in many complicated scenes.