Point tracking: an a-contrario approach

Abstract : In this work, we propose a new approach to recover trajectories from points previously detected in a sequence of images. In presence of spurious and missing detections, actual trajectories can be characterized by an a-contrario model, that estimates the probability of observing a similar trajectory in random data. This results in a single criterion combining trajectory characteristics (duration, number of points, smoothness) and data statistics (number of images and detected points), which can then be used to drive a dynamic programming algorithm able to extract sequentially the most meaningful trajectories. The performances obtained on synthetic and real-world data are studied in detail, and shown to compare favorably to the state-of-the-art ROADS algorithm.
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Pré-publication, Document de travail
MAP5 2012-06. 2012
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  • HAL Id : hal-00675083, version 1

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Maël Primet, Lionel Moisan. Point tracking: an a-contrario approach. MAP5 2012-06. 2012. 〈hal-00675083〉

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