Abstract
Vision-based human action recognition provides an advanced interface, and research in the field of human action recognition has been actively carried out. However, an environment from dynamic viewpoint, where we can be in any position, any direction, etc., must be considered in our living 3D space. In order to overcome the viewpoint dependency, we propose a Volume Motion Template(VMT) and Projected Motion Template (PMT). The proposed VMT method is an extension of the Motion History Image (MHI) method to 3D space. The PMT is generated by projecting the VMT into a 2D plane that is orthogonal to an optimal virtual viewpoint where the optimal virtual viewpoint is a viewpoint from which an action can be described in greatest detail, in 2D space. From the proposed method, any actions taken from different viewpoints can be recognized independent of the viewpoints. The experimental results demonstrate the accuracies and effectiveness of the proposed VMT method for view-independent human action recognition.
Original language | English |
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Title of host publication | Proceedings of the 2009 Chinese Conference on Pattern Recognition, CCPR 2009, and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR |
Pages | 832-836 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 2009 |
Event | 2009 Chinese Conference on Pattern Recognition, CCPR 2009 and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR - Nanjing, China Duration: 2009 Nov 4 → 2009 Nov 6 |
Publication series
Name | Proceedings of the 2009 Chinese Conference on Pattern Recognition, CCPR 2009, and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR |
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Other
Other | 2009 Chinese Conference on Pattern Recognition, CCPR 2009 and the 1st CJK Joint Workshop on Pattern Recognition, CJKPR |
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Country/Territory | China |
City | Nanjing |
Period | 09/11/4 → 09/11/6 |
Bibliographical note
Funding Information:This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government (MEST) (No. 2009-0060113 ).
Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
Keywords
- Human action recognition
- Motion history image
- View-independence
- Volume motion template
ASJC Scopus subject areas
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Software