实时鲁棒的频域空间目标跟踪方法

本文中实现了一种实时鲁棒的目标跟踪方法,提出了新颖的基于目标形状和外观的稠密循环采样方法、循环矩阵和频域空间的能量最小化目标跟踪方法。本文方法总体上减少了需要处理的数据量,尤其是加入了循环矩阵,极大地简化了计算过程,并将目标特征转换到高维频域空间进行了线性表示,最后用高频空间能量最小化的方法实现了更加快速和精准的目标跟踪。通过大量的对比实验表明,本文方法的总体效果较好,在目标朝向变化、场景光照变化、视频抖动、目标尺度模式变化、目标部分遮挡等环境下,较目前效果最好、最新的方法,本文方法在综合的跟踪精度和效率方面更能取得较好的效果。

Real-time and robust object tracking method in frequency domain space

This paper addresses real-time and robust object tracking method.In this paper,dense circulation sampling and frequency domain transform method were used in target tracking processing.This paper proposed energy minimization object tracking method in frequency domain space and put forward the concept of dense circulation sampling to solve object shape changes,appearance changes,object orientation changes,scene illumination changes,video jitter,objective scale changes and object occlusion problems in tracking processing.This method calculates a target by ten adjacent frames and circulation matrix in frequency domain space.This algorithm defines error as an energy function.This method proposed frequency domain energy minimum method firstly.Energy minimization make error between target and ground truth minimize.This algorithm can obtain more precision target results rapidly,so data quantity is sharp decreased.This algorithm use the dense circulation sampling and energy minimization method to implement a stable visual tracking in such situation as target orientation deformation,scene illumination changes,video stabilization,target scale transformation,target part occlusion.Compared with the latest and the best performance methods at present,the proposed method has significantly improved the tracking precision and efficiency.