Title
Human Action Recognition Employing Td2Dpca And Vq
Abstract
A novel algorithm for human action recognition in the transform domain is presented. This approach is based on Two- Dimensional Principal Component Analysis (2DPCA) and Vector Quantization (VQ). This technique reduces the computational complexity and the storage requirement by at least a factor of 45.27, and 12 respectively, while achieving the highest recognition accuracy, compared with the most recently published approaches. Experimental results applied on the Weizmann dataset confirm the excellent properties of the proposed algorithm, which lends itself to real-time economic implementation. © 2010 IEEE.
Publication Date
9-20-2010
Publication Title
Midwest Symposium on Circuits and Systems
Number of Pages
624-627
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/MWSCAS.2010.5548903
Copyright Status
Unknown
Socpus ID
77956570428 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/77956570428
STARS Citation
Naiel, Mohamed A.; Abdelwahab, Moataz M.; and Mikhael, Wasfy B., "Human Action Recognition Employing Td2Dpca And Vq" (2010). Scopus Export 2010-2014. 1014.
https://stars.library.ucf.edu/scopus2010/1014