Incremental action recognition using feature-tree

Action recognition methods suffer from many drawbacks in practice, which include (1)the inability to cope with incremental recognition problems; (2)the requirement of an intensive training stage to obtain good performance; (3) the inability to recognize simultaneous multiple actions; and (4) difficulty in performing recognition frame by frame. In order to overcome all these drawbacks using a single method, we propose a novel framework involving the feature-tree to index large scale motion features using Sphere/Rectangle-tree (SR-tree). The recognition consists of the following two steps: 1) recognizing the local features by non-parametric nearest neighbor (NN), 2) using a simple voting strategy to label the action. The proposed method can provide the localization of the action. Since our method does not require feature quantization, the feature-tree can be efficiently grown by adding features from new training examples of actions or categories. Our method provides an effective way for...

• Type: Journal
• Year: 2009
• Where: ICCV
• Authors: Kishore K. Reddy, Jingen Liu, Mubarak Shah
• Keywords: Action Recognition, Computer Vision, ICCV 2009, Incremental Recognition Problems, Large Scale