计算机应用研究2016，Vol.33Issue(4)：1245-1248,1261,5.DOI:10.3969/j.issn.1001-3695.2016.04.063
尺度自适应在线鲁棒目标跟踪
On-line robust object tracking with scale adaption
摘要
Abstract
To solve the shift problem that on-line boosting based tracking algorithm often faced due to substantial change of appearance and occlusion,this paper proposed a scale adaptive robust object tracking algorithm in this work.The algorithm achieved scale adaptive by analyzing the moments of the weight image that based on statistical features of gray scale or color histogram features.Then it introduced a semi-supervised strategy to solve the tracking failure during on-line updating.Video tests show that the proposed on-line robust tracking algorithm achieves robust tracking under the situation of occlusion,appea-rance change and scale variation.Compared with EM-shift,MIL and SPT algorithm,the proposed method exhibits higher accu-racy and robustness.关键词
在线boosting/半监督学习/尺度自适应/权重图像/目标跟踪Key words
on-line boosting/semi-supervised learning/scale adaption/weighted image/object tracking分类
信息技术与安全科学引用本文复制引用
王俊超,张东波,秦海,颜霜..尺度自适应在线鲁棒目标跟踪[J].计算机应用研究,2016,33(4):1245-1248,1261,5.基金项目
国家自然科学基金资助项目（60835004）；湖南省教育厅重点项目（14A137）；湖南省重点学科资助项目 （）
