Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6937654 | Computer Vision and Image Understanding | 2016 | 11 Pages |
Abstract
Experimental results on a challenging and realistic dataset show an improvement in action recognition performance of 16% due to the introduction of our hierarchical transfer learning. The proposed algorithm is fast with an average latency of just 2 frames (66Â ms) and outperforms state of the art action recognition algorithms that are capable of fast online action recognition.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Victoria Bloom, Vasileios Argyriou, Dimitrios Makris,