西安电子科技大学学报（自然科学版）Issue(3)：61-66,6.DOI:10.3969/j.issn.1001-2400.2015.03.011
利用超像素混合投票的在线目标跟踪算法
Online visual tracking method based on superpixel hybrid voting
摘要
Abstract
It is a great challenge to track an obj ect robustly when variations occur such as changes in illumination,appearance or partial occlusion. In this paper, we propose a target tracking algorithm combining superpixel and hybrid Hough voting.Local features are extracted from the context as supporters to construct a hybrid voting model.By this model,the target center is estimated by the Hough voting scheme.Local features are also distinguished to vote for the target and background,respectively.These voting results are combined into superpixels.Finally,the tracking task is formulated as the maximum a posterior estimate in the voting space.We demonstrate the performance of the algorithm on several public video sequences,which shows that our method is better than other online tracking approaches.关键词
目标跟踪/局部特征/目标分割/霍夫变换Key words
visual tracking/local features/segmentation/Hough transforms分类
信息技术与安全科学引用本文复制引用
贺文骅,刘志镜,屈鉴铭..利用超像素混合投票的在线目标跟踪算法[J].西安电子科技大学学报（自然科学版）,2015,(3):61-66,6.基金项目
国家自然科学基金资助项目(61173091) （61173091）
