CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Mean-Shift Tracking via a New Similarity Measure
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Real-Time Multiple Objects Tracking with Occlusion Handling in Dynamic Scenes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Selective-Attention Correlation Measure for Precision Video Tracking
IEICE - Transactions on Information and Systems
Fast occluded object tracking by a robust appearance filter
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual tracking and recognition using appearance-adaptive models in particle filters
IEEE Transactions on Image Processing
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Visual tracking is required by many vision applications such as human-computer interfaces and human-robot interactions. However, in daily living spaces where such applications are assumed to be used, stable tracking is often difficult because there are many objects which can cause the visual occlusion. While conventional tracking techniques can handle, to some extent, partial and short-term occlusion, they fail when presented with complete occlusion over long periods. They also cannot handle the case that an occluder such as a box and a bag contains and carries the tracking target inside itself, that is, the case that the target invisibly moves while being contained by the occluder. In this paper, to handle this occlusion problem, we propose a method for visual tracking by a particle filter, which switches tracking targets autonomously. In our method, if occlusion occurs during tracking, a model of the occluder is dynamically created and the tracking target is switched to this model. Thus, our method enables the tracker to indirectly track the “invisible target” by switching its target to the occluder effectively. Experimental results show the effectiveness of our method.