Robust detection and tracking pedestrian object for real time surveillance applications

Abstract

This paper describes about real-time moving pedestrian object detection and tracking. In this work, a new pedestrian object tracking approach is proposed, which uses a new texture model for better representing the pedestrian object. This approach based primarily on a step of object detection for automatic pedestrian object area extraction, features extraction step for pedestrian object representation and finally tracking step based on region matching method. We propose a new texture model for discriminant pedestrian object representation. This model based on a set of Haralick indexes computed from co-occurrence matrix. The presented approach can handle orientation, object scale, illumination changes, and clutter and complex occlusions.