Human action recognition using high-order feature of optical flows
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Information Systems,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s11227-021-03827-z.pdf
Reference42 articles.
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3. Wang, H, Kläser, A (2011) Cordelia Schmid, and Cheng-Lin Liu. Action recognition by dense trajectories. In: CVPR 2011, pp 3169–3176. IEEE
4. Wang, H, Schmid, C (2013) Action recognition with improved trajectories. In: Proceedings of the IEEE International Conference on Computer Vision, pp 3551–3558
5. Huang, Q, Sun, S, Wang, F (2017) A compact pairwise trajectory representation for action recognition. In: 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 1767–1771. IEEE
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