Human action recognition employing TD2DPCA and VQ

Author

Naiel, Mohamed A. ; Abdelwahab, Moataz M. ; Mikhael, Wasfy B.

Author_Institution

Sch. of Commun. & Inf. Technol., Nile Univ., 6th October City, Egypt

fYear

2010

Firstpage

624

Lastpage

627

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.

Keywords

computational complexity; image recognition; principal component analysis; vector quantisation; Weizmann dataset; computational complexity; human action recognition; two dimensional principal component analysis; vector quantization; Computational complexity; Feature extraction; Humans; Image recognition; Kinematics; Optical filters; Principal component analysis; Shape; Vector quantization; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems (MWSCAS), 2010 53rd IEEE International Midwest Symposium on

Conference_Location

Seattle, WA

ISSN

1548-3746

Print_ISBN

978-1-4244-7771-5

Type

conf

DOI

10.1109/MWSCAS.2010.5548903

Filename

5548903