Human Action Recognition from Inter-Temporal Dictionaries of Key-Sequences. Alfaro, A., Mery, D., & Soto, A. In 6th Pacific-Rim Symposium on Image and Video Technology, PSIVT, 2013.
Human Action Recognition from Inter-Temporal Dictionaries of Key-Sequences [pdf]Paper  abstract   bibtex   14 downloads  
This paper addresses the human action recognition in video by proposing a method based on three main processing steps. First, we tackle problems related to intraclass variations and differences in video lengths. We achieve this by reducing an input video to a set of key-sequences that represent atomic meaningful acts of each action class. Second, we use sparse coding techniques to learn a representation for each key-sequence. We then join these representations still preserving information about temporal relationships. We believe that this is a key step of our approach because it provides not only a suitable shared rep resentation to characterize atomic acts, but it also encodes global tem poral consistency among these acts. Accordingly, we call this represen tation inter-temporal acts descriptor. Third, we use this representation and sparse coding techniques to classify new videos. Finally, we show that, our approach outperforms several state-of-the-art methods when is tested using common benchmarks.

Downloads: 14