Fusion of Tracking Techniques to Enhance Adaptive Real-time Tracking of Arbitrary Objects

@inproceedings{Poschmann2014FusionOT,
  title={Fusion of Tracking Techniques to Enhance Adaptive Real-time Tracking of Arbitrary Objects},
  author={Peter Poschmann and Patrik Huber and Matthias R{\"a}tsch and Josef Kittler and Hans-Joachim B{\"o}hme},
  booktitle={IHCI},
  year={2014}
}
In visual adaptive tracking, the tracker adapts to the target, background, and conditions of the image sequence. Each update introduces some error, so the tracker might drift away from the target over time. To increase the robustness against the drifting problem, we present three ideas on top of a particle filter framework: An optical-flow-based motion estimation, a learning strategy for preventing bad updates while staying adaptive, and a sliding window detector for failure detection and… CONTINUE READING

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