Abstract
We present a novel framework to reliably learn scene entry and exit locations using coherent motion regions formed by weak tracking data. We construct “entities” from weak tracking data at a frame level and then track the entities through time, producing a set of consistent spatio-temporal paths. Resultant entity entry and exit observations of the paths are then clustered and a reliability metric is used to score the behavior of each entry and exit zone. We present experimental results from various scenes and compare against other approaches.
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Nedrich, M., Davis, J.W. (2010). Learning Scene Entries and Exits Using Coherent Motion Regions. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2010. Lecture Notes in Computer Science, vol 6453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17289-2_12
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DOI: https://doi.org/10.1007/978-3-642-17289-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-17288-5
Online ISBN: 978-3-642-17289-2
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