Sparsity-inducing dictionaries for effective action classification

Author:

Roy Debaditya,Srinivas M.,Krishna Mohan C.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference44 articles.

1. H. Wang, C. Schmid, Action recognition with improved trajectories, in: International Conference on Computer Vision (ICCV), Sydney, Australia, 2013, URL 〈http://hal.inria.fr/hal-00873267〉.

2. S. Sadanand, J. Corso, Action bank: a high-level representation of activity in video, in: IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012, pp. 1234–1241, http://dx.doi.org/10.1109/CVPR.2012.6247806.

3. C. Schuldt, I. Laptev, B. Caputo, Recognizing human actions: a local SVM approach, in: Proceedings of the 17th International Conference on Pattern Recognition (ICPR), vol. 3, IEEE Computer Society, Washington, DC, USA, 2004, pp. 32–36, http://dx.doi.org/10.1109/ICPR.2004.747, URL 〈http://dx.doi.org/10.1109/ICPR.2004.747〉.

4. I. Laptev, B. Caputo, 〈http://www.nada.kth.se/cvap/actions/〉.

5. A. Klaser, M. Marszalek, C. Schmid, A spatio-temporal descriptor based on 3d-gradients, in: British Machine Vision Conference (BMVC), 2008, pp. 275:1–10.

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