Abstract
We present a method for detecting common human actions in video, common to athletics and surveillance, using intuitive sketches and motion cues. The framework presented in this paper is an automated end-to-end system which (1) interprets the sketch input, (2) generates a query video based on motion cues, and (3) incorporates a new content-based action descriptor for matching. We apply our method to a publicly-available video repository of many common human actions and show that a video matching the concept of the sketch is generally returned in one of the top three query results.
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Suma, E.A., Sinclair, C.W., Babbs, J., Souvenir, R. (2008). A Sketch-Based Approach for Detecting Common Human Actions. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_40
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DOI: https://doi.org/10.1007/978-3-540-89639-5_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89638-8
Online ISBN: 978-3-540-89639-5
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