Saliency guided local and global descriptors for effective action recognition-Reference-Cited by-同舟云学术

Saliency guided local and global descriptors for effective action recognition

Published:2016-01-29 Issue:1 Volume:2 Page:97-106
ISSN:2096-0433
Container-title:Computational Visual Media
language:en
Short-container-title:Comp. Visual Media

Author:

Abdulmunem Ashwan,Lai Yu-Kun,Sun Xianfang

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition

Link

http://link.springer.com/content/pdf/10.1007/s41095-016-0033-9

Reference39 articles.

1. Kläser, A.; Marszalek, M.; Schmid, C. A spatiotemporal descriptor based on 3D-gradients. In: Proceedings of British Machine Vision Conference, 995–1004, 2008.

2. Scovanner, P.; Ali, S.; Shah, M. A 3-dimensional SIFT descriptor and its application to action recognition. In: Proceedings of the 15th ACM International Conference on Multimedia, 357–360, 2007.

3. Willems, G.; Tuytelaars, T.; Van Gool, L. An efficient dense and scale-invariant spatiotemporal interest point detector. In: Lecture Notes in Computer Science, Vol. 5303. Forsyth, D.; Torr, P.; Zisserman, A. Eds. Springer Berlin Heidelberg, 650–663, 2008.

4. Yuan, C.; Li, X.; Hu, W.; Ling, H.; Maybank, S. 3D R transform on spatiotemporal interest points for action recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 724–730, 2013.

5. Zhang, H.; Zhou, W.; Reardon, C.; Parker, L. Simplex-based 3D spatio-temporal feature description for action recognition. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2067–2074, 2014.

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