The work presented in this paper addresses the application of new technologies to the task of intruder monitoring. It presents an innovative Machine Vision application to detect and track a person in a Closed Circuit Television System (CCTV) identifying suspicious activity. Neural Network techniques are applied to identify suspicious activities from the trajectory path, speed, direction and risk areas for a person in a scene, as well as human posture. Results correlate well with operator determining suspicious activity. The automated system presented assists an operator to increase reliability and to monitor large numbers of surveillance cameras.
|Title of host publication||Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems|
|Publication status||Published - 1 Jan 2009|
- machine vision
- automatic intruder detection
- intruder monitoring