Research On Multiple Moving Target Detection And Tracking

Motion detection and tracking is one of the important area in digital image processing and pattern recognition research, as well one of the main elements in field of computer vision. It has broadly applied in robot navigation, security monitoring systems,medical image analysis and in the areas of virtual reality. The paper mainly researches motion detection and multi-target tracking technology.The paper introduces three algorithms on the motion detection including frame subtraction,background subtraction and optic flow method and give them comprehensive analysis of the advantages and disadvantages.In the condition of the camera is fixed, this paper takes the method of background subtraction to detect the moving target. Based on the frame subtraction, an improved method to acquire background is presented,as well the simulation of original method and improved method is given, the results indicate that the improved method achieves the expected effect.This paper uses the improved method to extract the background image automatically and then uses the background difference method to achieve the initial detection of moving targets.Finally, this paper takes the adoption of gray-scale image histogram equalization and morphological operation to dissociate all the moving targets completely.On the research of multi-target tracking, this paper gives the Kalman filter and tracking model a brief presentation and proposes a method of combining multi-feature fusion and Kalman prediction for multi-target tracking.The center of target's minimum bounding rectangle, the target's aspect, and the target's area are composed of integration measure, and this measure is taken to match the multiple moving targets. Experimental results show the good accuracy and stability of using this method to track multiple moving targets.