Improved Moving Object Detection And Tracking Based On Independent Component Analysis

With the development of the computer technology and digital image processing, moving object detection and tracking is gradually becoming a very important research subject of computer vision and is capturing more and more attention. It is widely utilized in such areas as robot vision navigation, intelligent transportation system, medical image processing, etc.In this paper, shadow detection technology together with moving object detection and tracking based on ICA are deeply researched. This paper mainly contained the following three parts:(1) A shadow detection method based on the invariant color characteristic was presented. By analyzing the present shadow detection methods, especially the methods which based on the color and texture information, this paper proposed a moving shadow detection method based on the invariant color characteristic. In this method, a step is firstly implemented to justify whether there exist shadow pixel in the current frame, then the potential shadow pixels are obtained through a preprocessing method, which reduced the disturbance to some extent; then the shadow pixels are confirmed by using the invariant color characteristic; Finally, the detection result is revised through the shadow pixels' geometrical characteristic. As a result, the comparatively accurate detection result is obtained.(2) The moving object detection method based on independent component analysis is improved in this paper. By analyzing the original moving object detection method, especially its faults, such as the low detection accuracy, without the ability to extract multiple moving targets, this paper improved and completed the target extraction part. The detection accuracy is increased by preprocessing the gray image and introducing the shadow illumination step. The multiple targets are extracted by implementing the extracting method in which the cylinder projection is done in alternated direction for three times.(3) The moving object tracking method using independent component analysis with reference is improved in this paper. On the basis of fully analyzing the algorithm and moving object tracking, the reason why the original method, in which the normalized 2-order center moment is used as reference, generated iteration error is obtained. Consequently, a new tracking method, in which the object to be tracked is used as reference, is presented in this paper. The moving object is tracked successfully through this method and the iteration error is effectively reduced. Furthermore, considering the instability caused by the illumination change in the process of object tracking, a further solution, in which the normalized singular value decomposition is introduced to measure the similarity between the reference and the estimation of the interested output signal, is proposed. As a result, the robustness of the tracking method is improved.The experimental results demonstrated the effectiveness of the proposed methods.