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Galilean-Diagonalized Spatio-Temporal Interest Operators
Cambridge UK August 23-August 26
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2004.133400417th International Conference on Patt ...
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Tony Lindeberg, Computational Vision and Active Perception Laboratory (CVAP), Sweden
Amir Akbarzadeh, Computational Vision and Active Perception Laboratory (CVAP), Sweden
Ivan Laptev, Computational Vision and Active Perception Laboratory (CVAP), Sweden
This paper presents a set of image operators for detecting regions in space-time where interesting events occur. To define such regions of interest, we compute a spatio-temporal second-moment matrix from a spatio-temporal scale-space representation, and diagonalize this matrix locally, using a local Galilean transformation in space-time, optionally combined with a spatial rotation, so as to make the Galilean invariant degrees of freedom explicit. From the Galilean-diagonalized descriptor so obtained, we then formulate different types of space-time interest operators, and illustrate their properties on different types of image sequences.
Citation:
Tony Lindeberg, Amir Akbarzadeh, Ivan Laptev, "Galilean-Diagonalized Spatio-Temporal Interest Operators," icpr, vol. 1, pp.57-62, 17th International Conference on Pattern Recognition (ICPR'04) - Volume 1, 2004
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