Exploring alternative spatial and temporal dense representations for action recognition
CAIP'11 Proceedings of the 14th international conference on Computer analysis of images and patterns - Volume Part II
A line based pose representation for human action recognition
Image Communication
Exploring trace transform for robust human action recognition
Pattern Recognition
Silhouette-based human action recognition using sequences of key poses
Pattern Recognition Letters
| Hi-index | 0.00 |
In this paper, we explore the idea of using only pose, without utilizing any temporal information, for human action recognition. In contrast to the other studies using complex action representations, we propose a simple method, which relies on extracting “key poses” from action sequences. Our contribution is two-fold. Firstly, representing the pose in a frame as a collection of line-pairs, we propose a matching scheme between two frames to compute their similarity. Secondly, to extract “key poses” for each action, we present an algorithm, which selects the most representative and discriminative poses from a set of candidates. Our experimental results on KTH and Weizmann datasets have shown that pose information by itself is quite effective in grasping the nature of an action and sufficient to distinguish one from others.