ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Scale & Affine Invariant Interest Point Detectors
International Journal of Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Spatiotemporal salient points for visual recognition of human actions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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A number of action recognition methods make use of spatio-temporal features. These features often consist of local spatio-temporal descriptors centered at locations provided by an interest point detector. The extracted descriptors will then serve as input to classification algorithms. The correct scale of these descriptors is an essential parameter to be determined. Improved information quality has been achieved from recently developed entropy-based spatio-temporal feature descriptors. In this paper, we present an approach for determining scales of the sub-volumes of interest given the locations of spatio-temporal features. Our method works by measuring the average variations of local motion content calculated on subsequences of motion filter responses. We design a filter-specific data prior that allows to determine the scales of the informative neighborhoods. We demonstrate that features calculated at the scales provided by or method allow for noticeable performance improvements of action recognition algorithms.