The Technology Of Moving Target Detection And Tracking In Dynamic Scene

The moving target detecting and tracking technology has become a hot topic in the fields of computer vision, image processing, pattern recognition, artificial intelligence and so on. It has already been used in many areas such as intelligent robot, intelligent transportation and video supervising. Usually the image sequences are classified into static one and dynamic one. The latter is more tally with practice and valuable in the domain of target detection and tracking based on image sequences, so target detection and tracking in dynamic scene is the important part for this research domain.This paper mainly researches the methods of detecting and tracking of moving target in image sequences acquired by a mobile camera. In order to improve the accuracy and velocity of the global estimation and compensation, an improved adaptive noise reduction method is proposed. Target area is obtained automatically which solves the problem that the target area needs to be determined artificially in traditional Mean Shift algorithm.The primary researches of this paper include sections as following:Firstly introduce the camera motion models. The motion of camera in spatial domain is analyzed, and the typical camera motion model: the eight parameters model based on perspective projection and the six parameters model based on parallel projection are also introduced.Then the method based on feature is used for global motion estimation. The SIFT algorithm is applied for getting high accurate and stable features. In order to improve the accuracy of global estimation and compensation, it is necessary to eliminate points with local motion. An improved adaptive noise reduction method is proposed in this paper, which is effective demonstrated by the experimental results.Frame difference is used to detect moving target in dynamic scene. The motion compensation for the two frame images is done at first to get a similar background according to the estimated global motion parameters of two frame images. Then moving target is detected by the difference between the compensated image and the reference image.Finally the MRF segmentation algorithm is used for segmenting the difference images. In this paper, the holes and the edges are filled through closing operation in the field of mathematical morphology, after that, a binary image including complete target area is obtained. Then, a target template is got via mapping the coordinates of the horizontal projection and perpendicular projection vertexes to the corresponding original images. Finally, target area is picked up automatically which solves the problem that the target area needs to be determined artificially in traditional Mean Shift algorithm, and automatic target tracking is realized.