Structured partial least squares for simultaneous object tracking and segmentation

In this paper, we propose a novel method to address this limitation by incorporating structured labeling information in the partial least square analysis algorithms for simultaneous object tracking and segmentation. This allows for novel structured labeling constraints to be placed directly on the tracked objects to provide useful contour constraint to alleviate the drifting problem. We show through both visual results and quantitative measurements on the challenging sequences that our method produces more robust tracking results while obtaining accurate object segmentation results.