Real-Time Intruder Detection in Surveillance Networks Using Adaptive Kernel Methods

Author

Ahmed, Tarem ; Ahmed, Sabrina ; Ahmed, Supriyo ; Motiwala, Murtaza

Author_Institution

Dept. of Electr. & Electron. Eng., BRAC Univ., Dhaka, Bangladesh

fYear

2010

fDate

23-27 May 2010

Firstpage

1

Lastpage

5

Abstract

In this paper we apply a recursive algorithm based on kernel mappings to propose an automated, real-time intruder detection mechanism for surveillance networks. Our proposed method is portable and adaptive, and does not require any expensive or sophisticated components. Through application to real images from BRAC University´s closed-circuit television system and comparison with common methods based on Principle Component Analysis (PCA), we show that it is possible to obtain high detection accuracy with low complexity.

Keywords

closed circuit television; principal component analysis; telecommunication security; video surveillance; PCA; adaptive kernel methods; closed-circuit television system; principle component analysis; realtime intruder detection; surveillance networks; Adaptive systems; Dictionaries; Kernel; Machine learning algorithms; Principal component analysis; Roads; Support vector machines; Surveillance; TV; Vehicle detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications (ICC), 2010 IEEE International Conference on

Conference_Location

Cape Town

ISSN

1550-3607

Print_ISBN

978-1-4244-6402-9

Type

conf

DOI

10.1109/ICC.2010.5502592

Filename

5502592