基于特征点集群目标跟踪与检测

目标跟踪与检测技术是计算机视觉研究领域一个热点和难点问题，该技术广泛应用在制导、导航、监控等方面。尤其在复杂背景下，准确的跟踪既定目标，在遮挡情况下稳定跟踪，是近年来研究的热点。利用一种特征点集群方法，通过提取特征点方式，以及对目标的运动估计等方式，解决针对地面目标在光线变化、缩放、旋转3个变化量下的跟踪与检测问题。该方法对于地面运动目标的限制较小，同时图像序列中每一帧图像间运动目标的位移量较小。运用本文所提出算法，能够解决针对地面目标在光线变化、缩放以及旋转情况下跟踪与检测的问题。

Base on cluster feature tracking and detection

Target tracking and detection technology is a hot and difficult problem in the field of computer vision research, which is widely used in guidance, navigation, monitoring and so on. Especially in the complex background, the accurate tracking of the target, in the occlusion of the stable tracking, is a hot research topic in recent years. By using a feature point cluster method, extracting feature points and estimating the target motion etc., solve the ground target under the light changes, scaling, rotation, and three variations of tracking and detection. This method has less limitation to the ground moving target, and the displacement of the moving object is smaller in the image sequence at the same time. By using the proposed algorithm, we can solve the problem of tracking and detecting the ground targets in the case of light variation, scaling and rotation.