PROJECT TITLE :

A Genetic Algorithm-Based Moving Object Detection for Real-time Traffic Surveillance

ABSTRACT:

Recent developments in vision systems like distributed smart cameras have encouraged researchers to develop advanced laptop vision applications suitable to embedded platforms. In the embedded surveillance system, where memory and computing resources are restricted, easy and economical laptop vision algorithms are needed. During this letter, we tend to present a moving object detection technique for real-time traffic surveillance applications. The proposed methodology may be a combination of a genetic dynamic saliency map (GDSM), which is an improved version of dynamic saliency map (DSM) and background subtraction. The experimental results show the effectiveness of the proposed methodology in detecting moving objects.