CAJ | 학술논문

针对传统均值漂移算法(Mean shift)中核函数直方图对目标特征描述较弱、跟踪过程中核函数带宽的保持不变的缺点,提出了一种新的核函数带宽可变的Mean shift跟踪算法.在特定的色彩空间中,统计落入各区间的像素个数.并对各区间像素的位置建立高斯分布模型,采用二阶空间直方图实现目标建模,强化目标特征描述提高了跟踪的鲁棒性;结合边缘检测与角点检测选取目标特征点估算目标仿射模型确定伸缩尺度.适应目标多自由度变化下的跟踪.实验结果证明,该算法比原有算法跟踪效果更加准确和可靠.
침대전통균치표이산법(Mean shift)중핵함수직방도대목표특정묘술교약、근종과정중핵함수대관적보지불변적결점,제출료일충신적핵함수대관가변적Mean shift근종산법.재특정적색채공간중,통계락입각구간적상소개수.병대각구간상소적위치건립고사분포모형,채용이계공간직방도실현목표건모,강화목표특정묘술제고료근종적로봉성;결합변연검측여각점검측선취목표특정점고산목표방사모형학정신축척도.괄응목표다자유도변화하적근종.실험결과증명,해산법비원유산법근종효과경가준학화가고.
The traditional Mean shift is invariable bandwidth and cannot represent accurately the color distribution of the object. To improve theoretical limitation, a novel target tracking algorithm within the framework of Mean shift is presented. Firstly, a new color space of the object is partitioned into subspaces by considering the weighted number of pixels with feature vectors cluster, and describing the pixel coordinates with Gaussian distribution. Then, an improved spatiograms is adopted to describe the reference model and the candidate model, and Bhattacharyya distance is derived to evaluate the similarity between them. Finally, the affine transform is established by combining corner and edge detector to calculate scale parameter. The algorithm is proved to have better effect and robust through experiments.