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. © 2010 Springer-Verlag.
CITATION STYLE
Nedrich, M., & Davis, J. W. (2010). Learning scene entries and exits using coherent motion regions. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6453 LNCS, pp. 120–131). https://doi.org/10.1007/978-3-642-17289-2_12
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