Abstract: A simple and efficient moving object detection and tracking algorithm is proposed. The object detection is based on the background subtraction method; an adaptive local threshold selection method on the use of entropy power and GGD (Generalized Gaussian distribution) is proposed to get over the noise influence. Feature based tracking method is used in object tracking. A feature named LICS (Logarithm illuminance contrast statistic) is proposed, which can effectively represent the objects' appearance. Tracking of rigid objects by LICS is stable when the objects' illumination and posture are variable. The Kalman filter is used to restrict the search window and reduce the calculation. A sub-block matching algorithm is used to handle the objects occlusion. The experimental results show that the proposed algorithm has good performance.