Abstract
In this paper a novel view-independent human action recognition method is proposed. A multi-camera setup is used to capture the human body from different viewing angles. Actions are described by a novel action representation, the so-called multi-view action image (MVAI), which effectively addresses the camera viewpoint identification problem, i.e., the identification of the position of each camera with respect to the person's body. Linear Discriminant Analysis is applied on the MVAIs in order to to map actions to a discriminant feature space where actions are classified by using a simple nearest class centroid classification scheme. Experimental results denote the effectiveness of the proposed action recognition approach.
| Original language | English |
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| Title of host publication | 2013 IEEE 11th IVMSP Workshop: 3D Image/Video Technologies and Applications, IVMSP 2013 - Proceedings |
| DOIs | |
| Publication status | Published - 2013 |
| Publication type | A4 Article in conference proceedings |
| Event | 2013 IEEE 11th Workshop on 3D Image/Video Technologies and Applications, IVMSP 2013 - Seoul, Korea, Republic of Duration: 10 Jun 2013 → 12 Jun 2013 |
Conference
| Conference | 2013 IEEE 11th Workshop on 3D Image/Video Technologies and Applications, IVMSP 2013 |
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| Country/Territory | Korea, Republic of |
| City | Seoul |
| Period | 10/06/13 → 12/06/13 |
Keywords
- Discriminant Learning
- Human Action Recognition
- Multi-camera Setup
- Multi-view Action Images
ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Computer Vision and Pattern Recognition
- Computer Science Applications