Security Based on Real Time Tracking of Multiple Human Faces Identification

Full Text (PDF, 405KB), PP.85-92

Views: 0 Downloads: 0

Author(s)

V.K. Narendira Kumar 1,* B. Srinivasan 2

1. Department of Information Technology, Gobi Arts & Science College (Autonomous), Gobichettipalayam – 638 453, Erode District, Tamil Nadu, India

2. PG & Research Department of Computer Science, Gobi Arts & Science College (Autonomous), Gobichettipalayam – 638 453, Erode District, Tamil Nadu, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2013.05.10

Received: 5 Jun. 2012 / Revised: 23 Sep. 2012 / Accepted: 10 Nov. 2012 / Published: 8 Apr. 2013

Index Terms

Face, Skin, Color, Shadow, Tracking, Noise Filtering

Abstract

Robust tracking of persons in real-world environments and in real-time is a common goal in many video applications. In this paper a computational system for the real-time tracking of multiple persons in natural environments is presented. Face detection has diverse applications especially as an identification solution which can meet the crying needs in security areas. The region extractor is based on the integration of skin-color, motion and silhouette features, while the face detector uses a simple, rule-based face detection algorithm and SVM. Exemplary results of the integrated system working in real-world video sequences. New intelligent processing methods, as well as security requirements make multiple-person tracking a hot area. This application is robust tracking in real-world environments and in real-time.

Cite This Paper

V.K. Narendira Kumar, B. Srinivasan, "Security Based on Real Time Tracking of Multiple Human Faces Identification", International Journal of Intelligent Systems and Applications(IJISA), vol.5, no.5, pp.85-92, 2013. DOI:10.5815/ijisa.2013.05.10

Reference

[1]A. K. Jain, R. Bolle, “Biometric personal identification in networked society” 1999, Norwell, MA: Kluwer.

[2]C.Hesher, A.Srivastava, G.Erlebacher, “A novel technique for face recognition using range images” in the Proceedings of Seventh International Symposium on Signal Processing and Its Application, 2003.

[3]Baoxin Li and Rama Chellappa, “A generic approach to simultaneous tracking and verification in video,” IEEE Transactions on Image Processing, vol. 11, no. 5, pp. 530–544, May 2002.

[4]Christophe Garcia and Georgios Tziritas, “Face detection using quantized skin color regions merging and wavelet packet analysis,” IEEE Transactions on Multimedia, vol. 1, no. 3, pp. 264–277, September 1999.

[5]Dominique Valentin, Herve Abdi, Alice J. O’Toole, and Garrison W. Cottrell, “Connectionist models of face processing: A survey,” Pattern Recognition, vol. 27, pp. 1209–1230, 1994.

[6]Rein-Lien Hsu, Mohamed Abdel-Mottaleb, and Anil K. Jain, “Face detection in color images,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 696–706, May 2002.

[7]W. Zhao, R. Chellappa, A. Rosenfeld, and P.J. Phillips, Face Recognition: A Literature Survey, UMD CAFR, Technical Report, CAR-TR-948, October 2000.

[8]Lian Hock Koh, Surendra Ranganath, and Y.V. Venkatesh, “An integrated automatic face detection and recognition system,” Pattern Recognition, vol. 35, pp. 1259–1273, 2002.

[9]Ming-Hsuan Yang, David J. Kriegman, and Narendra Ahuja, “Detecting faces in images: A survey,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 1, pp. 34–58, January 2002.