Title
Human Action Recognition Employing 2Dpca And Vq In The Spatio-Temporal Domain
Abstract
In this paper a novel algorithm for human action recognition is presented. This approach is based on Two-Dimensional Principal Component Analysis (2DPCA) and Vector Quantization (VQ) in the spatial-temporal domain. This method reduces computational complexity by a factor of 98, while maintaining the storage requirement and the recognition accuracy, compared with some of the most recent approaches in the field. Experimental results applied on the Weizmann dataset confirm the excellent properties of the proposed algorithm. © 2010 IEEE.
Publication Date
11-22-2010
Publication Title
Proceedings of the 8th IEEE International NEWCAS Conference, NEWCAS2010
Number of Pages
381-384
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/NEWCAS.2010.5604002
Copyright Status
Unknown
Socpus ID
78349266174 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/78349266174
STARS Citation
Naiel, Mohamed A.; Abdelwahab, Moataz M.; and Mikhael, Wasfy B., "Human Action Recognition Employing 2Dpca And Vq In The Spatio-Temporal Domain" (2010). Scopus Export 2010-2014. 510.
https://stars.library.ucf.edu/scopus2010/510