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Hybrid framework for evaluating video object tracking algorithms

Hybrid framework for evaluating video object tracking algorithms

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A simple and efficient hybrid framework for evaluating algorithms for tracking objects in video sequences is presented. The framework unifies state-of-the-art evaluation metrics with diverse requirements in terms of reference information, thus overcoming weaknesses of individual approaches. With foundations on already demonstrated and well known metrics, this framework assumes the role of a flexible and powerful tool for the research community to assess and compare algorithms.

References

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      • Cavallaro, A., Ziliani, F.: `Characterisation of tracking performance', Proc. Workshop on Image Analysis For Multimedia Interactive Services (WIAMIS), Montreux, Switzerland, 2005.
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      • Black, J., Ellis, T., Rosin, P.: `A novel method for video tracking performance evaluation', Joint IEEE Int. Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance (VSPETS), Nice, France, 2003, p. 125–132.
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      • Bashir, F., Porikli, F.: `Performance evaluation of object detection and tracking systems', Proc. IEEE Int. Workshop on Performance Evaluation of Tracking and Surveillance (PETS), New York, USA, 2006, p. 7–14.
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