Title :
A neural network based intelligent intruders detection and tracking system using CCTV images
Author :
Fung, Chun Che ; Jerrat, Nicholas
Author_Institution :
Sch. of Electr. & Comput. Eng., Curtin Univ. of Technol., Bentley, WA, Australia
Abstract :
This paper reports the development of a neural network based intelligent intruders detection and tracking system using closed-circuit television (CCTV) images. It examines the techniques and algorithms used to identify a potential intruder and methods to eliminate other non-threatening objects. Once the presence of an intruder is determined, the object will be monitored and tracked. The tracked information can be used to further identify any suspicious behaviour in the sparse and complex environments. The traditional approach to intelligent scene monitoring (ISM) is examined and compared with the artificial neural network (ANN) approach. The ANN approach demonstrates how a system can learn how to distinguish suspicious movements from non-suspicious movements. The proposal has a potential to be used as an intelligent surveillance system
Keywords :
closed circuit television; computerised monitoring; image motion analysis; learning (artificial intelligence); perceptrons; surveillance; tracking; video signal processing; ANN; CCTV images; artificial neural network; closed-circuit television; intelligent intruders detection system; intelligent intruders tracking system; intelligent scene monitoring; intelligent surveillance system; neural network training; nonsuspicious movements; object monitoring; object tracking; straight-through perceptron neural network; suspicious movements; video motion detection; Artificial intelligence; Artificial neural networks; Intelligent networks; Intelligent systems; Layout; Monitoring; Neural networks; Proposals; Surveillance; TV;
Conference_Titel :
TENCON 2000. Proceedings
Conference_Location :
Kuala Lumpur
Print_ISBN :
0-7803-6355-8
DOI :
10.1109/TENCON.2000.888772