Improving the Robustness of Parametric Shape Tracking with Switched Multiple Models

This paper addresses the problem of tracking objects with complex motion dynamics or shape changes. It is assumed that some of the visual features detected in the image (e.g., edge strokes) are outliers i.e., they do not belong to the object boundary. A robust tracking algorithm is proposed which allows to e3ciently track an object with complex shape or motion changes in clutter environments. The algorithm relies on the use of multiple models, i.e., a bank of stochastic motion models switched according to a probabilistic mechanism. Robust 4ltering methods are used to estimate the label of the active model as well as the state trajectory. ? 2002 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.

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