Nested Motion Descriptors

Jeffrey Byrne; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 502-510

Abstract


A nested motion descriptor is a spatiotemporal representation of motion that is invariant to global camera translation, without requiring an explicit estimate of optical flow or camera stabilization. This descriptor is a natural spatiotemporal extension of the nested shape descriptor to the representation of motion. We demonstrate that the quadrature steerable pyramid can be used to pool phase, and that pooling phase rather than magnitude provides an estimate of camera motion. This motion can be removed using the log-spiral normalization as introduced in the nested shape descriptor. Furthermore, this structure enables an elegant visualization of salient motion using the reconstruction properties of the steerable pyramid. We compare our descriptor to local motion descriptors, HOG-3D and HOG-HOF, and show improvements on three activity recognition datasets.

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[bibtex]
@InProceedings{Byrne_2015_CVPR,
author = {Byrne, Jeffrey},
title = {Nested Motion Descriptors},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}