CAJ | 학술논문

在线目标跟踪是一个具有挑战性的问题。当运动目标表面发生变化、背景光线剧烈变化、背景物体的遮挡以及运动造成的模糊时，需要建立一个有效的物体外在表示模型。为此，本文利用典型的主成分分析( PCA)与稀疏表示建立了有效的观测模型。将詛1最小值引入到PCA重建中，将目标物体表示为主要特征和噪声之和的形式。除此之外，当发生遮挡和运动模糊时，为了减少跟踪漂移现象，该文提出了一种新的更新模型而不是简单的对观测模型直接更新。实验证明，该算法在目标物体发生遮挡以及背景光线发生剧烈变化时，对目标跟踪具有较强的鲁棒性。在评价指标重叠率和中心误差方面，算法跟踪精确度明显提高。
재선목표근종시일개구유도전성적문제。당운동목표표면발생변화、배경광선극렬변화、배경물체적차당이급운동조성적모호시，수요건립일개유효적물체외재표시모형。위차，본문이용전형적주성분분석( PCA)여희소표시건립료유효적관측모형。장저1최소치인입도PCA중건중，장목표물체표시위주요특정화조성지화적형식。제차지외，당발생차당화운동모호시，위료감소근종표이현상，해문제출료일충신적경신모형이불시간단적대관측모형직접경신。실험증명，해산법재목표물체발생차당이급배경광선발생극렬변화시，대목표근종구유교강적로봉성。재평개지표중첩솔화중심오차방면，산법근종정학도명현제고。
Online target tracking is a challenging problem. When the surface of moving target changes and the fuzzy caused by background object’s shelter and movement appears,it is necessary to establish an ef-fective external representation model of object. Thus, by taking advantage of the typical principal compo-nent analysis ( PCA) and sparse representation, an effective observation model is established. And by in-troducing L1 minimum value into the reconstruction of PCA, the target object is expressed as the sum of the major characteristic and the noise. In addition, when the shade and motion blur, in order to reduce the tracking drifting phenomenon, a novel model is proposed instead of simply updating the observation model. Experiments show that when the target object is covered and the background light changes dramatically, the algorithm is of strong robustness in target tracking. In overlap rate of evaluation index and center error, the algorithm is significantly improred in tracking accuracy.