Robust, real time people tracking with shadow removal in open environment

This paper presents a framework to track people using wavelet transform and Kalman filter in unconstrained environments. We adopt simultaneously the maximum and minimum variances of the color information in the trunk part of the tracked people to be the tracked features. However, the shadow is one of the environmental factors influencing on processing of monitored images. To make the system more robust, a shadow-removal scheme is devised. A multi-resolution method and the color information are used to eliminate shadows. The Kalman filter and DSA is adopted to be the estimator in this system. Experiments show that the proposed system achieves optimal performance in the complicated backgrounds.