Interactive Tracking of 2D Generic Objects with Spacetime Optimization
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Mean Shift tracking with multiple reference color histograms
Computer Vision and Image Understanding
Augmenting appearance-based localization and navigation using belief update
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 2 - Volume 2
Analytical dynamic programming tracker
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Upper Body Detection and Tracking in Extended Signing Sequences
International Journal of Computer Vision
A dynamic programming approach to maximizing tracks for structure from motion
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part II
Analytical dynamic programming matching
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part I
Efficiently Scaling up Crowdsourced Video Annotation
International Journal of Computer Vision
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A new approach to template tracking is presented, incorporating three distinct contributions. Firstly, an explicit definition for a feature track is given. Secondly, the advantages of an image preprocessing stage are demonstrated and, in particular, the effectiveness of highly compressed image patch data stored in k-d trees for fast and discriminatory image patch searches. Thirdly, the k-d trees are used to generate multiple track hypotheses which are efficiently merged to give the optimal solution using dynamic programming. The explicit separation of feature detection and trajectory determination creates the basis for the novel use of k-d trees and dynamic programming. Multiple appearances and occlusion handling are seamlessly integrated into this framework. Appearance variation through the sequence is robustly handled in an iterative process. The work presented is a significant foundation for a powerful off-line feature tracking system, particularly in the context of interactive applications.