Human action recognition has evoked considerable interest in the various research areas and applications due to its potential use in proactive computing. The objective of this work is to recognize various human actions like run, jump, walk etc. Moving Object detection and tracking is the first step for action recognition. The algorithm first makes use of the statistical background model and background subtraction method to extract the human action silhouettes. After extracting the silhouttes action recognition is done using template matching algorithm. Template matching algorithm employs correlation measure to find the similarity between the template and the given input.
[1]
S. Maheswari, Department of CSE, Manonmaniam Sundaranar University, Tirunelveli, India.
[2]
P. Arockia Jansi Rani, Department of CSE, Manonmaniam Sundaranar University, Tirunelveli, India.
[1]
Haritaoglu, D. Harwood, and L. S. Davis, “ Real-time surveillance of people and their activities”, IEEE T-PAMI, 22:809–830, 2000
[2]
W. Hu, T. Tan, L. Wang, and S. Maybank. “A survey on visual surveillance of object motion and behaviors”, IEEE Transactions on Systems, Man and Cybernetics, 34:334–352, 2004.
[3]
M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Basri, “Actions as space-time shapes”, In ICCV, 2005.
[4]
Marko Heikkila and Matti Pietika inen, Senior Member, IEEE, “A Texture-Based Method for Modeling the Background and Detecting Moving Objects” IEEE Transactions On Pattern Analysis And Machine Intelligence,Vol. 28,No. 4,April 2006
[5]
Z. Zhang, Y. Hu, S. Chan, and L.-T. Chia. “Motion context: A new representation for human action recognition” In ECCV, 2008.
[6]
Senior. “An introduction to automatic video surveillance. In Protecting Privacy in Video Surveillance” Springer, 2009.
[7]
Salem Saleh Al-amri, N.V. Kalyankar and Khamitkar S.D, “Image Segmentation by Using Thershod Techniques” Journal Of Computing, Volume 2, Issue 5, May 2010.
[8]
M.I.Khalil, “Car Plate Recognition Using the Template Matching Method”, International Journal of Computer Theory and Engineering, Vol. 2, No. 5, October, 2010.
[9]
O. BARNICH and M. VAN DROOGENBROECK, “ViBe: A universal background subtraction algorithm for video sequences” IEEE Transactions on Image Processing, 20(6): 1709-1724, June 2011.
[10]
Keigo Takahara, Takashi Toriu and Thi Thi Zin “Making Background Subtraction Robust to Various Illumination Changes” IJCSNS International Journal of Computer Science and Network Security, VOL.11 No.3, March 2011
[11]
Rupali S.Rakibe, Bharati D.Patil “Background Subtraction Algorithm Based Human Motion Detection” International Journal of Scientific and Research Publications, Volume 3, Issue 5, May 2013.