Entropy-based motion segmentation from a moving platform

Authors:
Hyeun Jeong Min;Nikolaos Papanikolopoulos
Affiliations:
Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN;Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN
Venue:
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Year:
2009

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Abstract

The forward moving target segmentation from a moving platform with a pinhole camera is an important and relatively unexplored problem in visual tracking. This paper proposes a novel segmentation algorithm for extracting a moving target when using a moving platform (that follows a similar trajectory and has a camera that is not calibrated for the particular scene). When the target has unpredictable motions, we are unable to model it and the pertinent backgrounds are very different. We introduce a new entropy-based clustering algorithm in order to find a bounding box representing the target. A target model based on graph representation is used for matching the moving target. To demonstrate the robust target segmentation scheme, we apply the method to a team of miniature robots (the Explorers developed at the University of Minnesota) in real tracking missions.