外文翻译一个鲁棒基于机器视觉运动目标检测与跟踪系统.docxVIP

附录I外文文献翻译(1)原文：A Robust Vision-based Moving Target Detection and Tracking System Abstract In this paper we present a new algorithm for real~time detection and tracking of moving targets in terrestrial scenes using a mobile camera. Our algorithm consists of two modes: detection and tracking. In the detection mode, background motion is estimated and compensated using an affine transformation. The resultant motion rectified image is used for detection of the target location using split and merge algorithm. We also checked other features for precise detection of the target location. When the target is identified, algorithm switches to the tracking mode. Modified Moravec operator is applied to the target to identify feature points. The feature points are matched with points in the region of interest in the current frame. The corresponding points are further refined using disparity vectors. The tracking system is capable of target shape recovery and therefore it can successfully track targets with varying distance from camera or while the camera is zooming. Local and regional computations have made the algorithm suitable for real-time applications. The refined points define the new position of the target in the current frame. Experimental results have shown that the algorithm is reliable and can successfully detect and track targets in most cases. Key words: real time moving target tracking and detection, feature matching, affine transformation, vehicle tracking, mobile camera image.1 Introduction Visual detection and tracking is one of the most challenging issues in computer vision. Application of the visual detection and tracking are numerous and they span a wide range of applications including surveillance system, vehicle tracking and aerospace application, to name a few. Detection and tracking of abstract targets (e.g. vehicles in general) is a very complex problem and demands sophisticated solutions using conventional pattern recognition and motion estimation m