A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Tracking via Level Set PDEs without Motion Computation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge Detection and Ridge Detection with Automatic Scale Selection
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
A Variational Framework for Joint Segmentation and Registration
MMBIA '01 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA'01)
Towards a Mathematical Theory of Primal Sketch and Sketchability
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Learning to Detect Natural Image Boundaries Using Local Brightness, Color, and Texture Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
Keyframe-based tracking for rotoscoping and animation
ACM SIGGRAPH 2004 Papers
Contour-Based Object Tracking with Occlusion Handling in Video Acquired Using Mobile Cameras
IEEE Transactions on Pattern Analysis and Machine Intelligence
Supervised Learning of Edges and Object Boundaries
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
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In this paper, we discuss an integrated system for video rotoscoping extracting and tracking object sketch (structural shape) across video sequence. This system consists of two key components: object sketch computing and graph-based object tracking. Given a video clip, we first use a primal sketch algorithm to search bottom-up sketch proposals and additively pursue sketch strokes in each frame. User is allowed to edit the sketch in the beginning frame, such as adding strokes and removing the cluttered edges, and the refined sketch is saved as the template. A graph-based tracking method is then proposed for sequentially matching the template to following frames, and the template is kept update by geometric transformation. Once the matching is unsatisfied at one frame, the system is allowed the user interaction for correction. In the experiments, we apply this system on several videos and present the performance evaluation with comparison.