中文摘要：

一个方法被介绍实现通过全向的视觉检测并且追踪动人的目标。方法把光流动与粒子过滤器算术，光流动地在被用来检测并且定位动人的目标相结合，粒子过滤器被用来追踪检测动人的对象。根据全向的视觉的圆形的图象特性的意见，光流动地的计算方程和粒子过滤器的追踪的算术在全向的中心基于极的坐标被改进。一个随机动人的对象的边能由光流动地被检测并且被一个引用区域在粒子过滤器包围。一个动态运动模型被建立预言粒子状态。直方图在参考区域和候选人区域被用作特征。相互的信息(MI ) 和 Gaussian 功能被联合计算粒子重量。最后，追踪的目标的状态与重量由全部的粒子状态被计算。建议方法能检测并且追踪移动的实验结果表演与更好即时的性能和精确性反对。

英文摘要：

A method was presented to implement the detecting and tracking of moving targets through omnidirectional vision. The method combined optical flow with particle filter arithmetic, in which optical flow field was used to detect and locate moving targets and particle filter was used to track the detected moving objects. According to the circular image character of omnidirectional vision, the calculation equation of optical flow field and the tracking arithmetic of particle filter were improved based on the polar coordinates at the omnidirectional center. The edge of a randomly moving object could be detected by optical flow field and was surrounded by a reference region in the particle filter. A dynamic motion model was established to predict particle state. Histograms were used as the features in the reference region and candidate regions. The mutual information （MI） and Gaussian function were combined to calculate particle weights. Finally, the state of tracked object was computed by the total particle states with weights. Experiment results show that the proposed method could detect and track moving objects with better realtime performance and accuracy.