CAJ | 학술논문

目标编码系数的稀疏性使得 L1跟踪成为解决遮挡目标跟踪的有效方法之一，但是现有稀疏编码算法没有利用 L1跟踪中编码系数的特殊稀疏结构。本文基于目标模板系数稀疏度约束要求和小模板系数的空间连续性结构，利用块坐标优化原理提出一种两阶段稀疏编码算法用于视觉跟踪。在第一阶段，该算法利用正交匹配追踪求解具有约束稀疏度的目标模板系数，在第二阶段，该算法利用动态组稀疏编码求解具有空间连续性的小模板系数。在粒子滤波框架下，利用提出的稀疏编码算法实现了鲁棒的视觉跟踪。实验结果表明本文提出的跟踪方法比现有跟踪方法具有更强的鲁棒性和较高的跟踪精度。
목표편마계수적희소성사득 L1근종성위해결차당목표근종적유효방법지일，단시현유희소편마산법몰유이용 L1근종중편마계수적특수희소결구。본문기우목표모판계수희소도약속요구화소모판계수적공간련속성결구，이용괴좌표우화원리제출일충량계단희소편마산법용우시각근종。재제일계단，해산법이용정교필배추종구해구유약속희소도적목표모판계수，재제이계단，해산법이용동태조희소편마구해구유공간련속성적소모판계수。재입자려파광가하，이용제출적희소편마산법실현료로봉적시각근종。실험결과표명본문제출적근종방법비현유근종방법구유경강적로봉성화교고적근종정도。
L1 tracker is one of the most effective methods in dealing with the occlusions for sparseness of coding coefficients of objects. However, the existing sparse coding algorithms do not use special sparse structure of coding coefficients in L1 tracker. In this paper, we propose a two-stage sparse coding algorithm for visual tracking based on constrained sparsity of target template coefficients and spatial continuity structure of trivial template coefficients with block coordinate optimization theory. At the first stage, the algorithm solves sparsity-constrained coding coefficients on target template set using orthogonal matching pursuit. At the second stage,the algorithm finds sparse coding coefficients with spatial continuity on trivial template set via dynamic group sparse coding. Robust visual tracking is achieved using the proposed sparse coding algorithm in particle filter framework. The experimental results demonstrate that the proposed tracking method has better robustness and higher precision than the state-of-the-art trackers.