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Abstract

Interactions between targets have been exploited to solve the occlusion problem in multitarget tracking but not to provide higher level scene understanding. As indoor environments are relatively unconstrained than urban areas, interactions in indoor environments are weaker and have more variants. Weak interactions make scene interaction modeling and neighboring object interaction modeling challenging. In this paper, a place-driven scene interaction model is proposed to represent long-term interactions in indoor environments. To deal with complicated short-term interactions, the neighboring object interaction model consists of three short-term interaction models, following, approaching and avoidance. The moving model, the stationary process model and these two interaction models are integrated to accomplish weakly interacting object tracking. In addition, higher level scene understanding such as unusual activity recognition and important place identification is accomplished straightforwardly. The experimental results using data from a laser scanner demonstrate the feasibility and robustness of the proposed approaches.

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Bibtex

@inproceedings{Wan_arso08,     author = {Kao-Wei Wan and Chieh-Chih Wang and Tu T. Ton},     title = {Weakly Interacting Object Tracking in Indoor Environments},     booktitle = {IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO)},     address = {Taipei, Taiwan},     month = {August},     year = {2008}, }