西安电子科技大学学报（自然科学版）2017，Vol.44Issue(4)：86-94,111,10.DOI:10.3969/j.issn.1001-2400.2017.04.016
一种利用物体性检测的目标跟踪算法
Object tracking algorithm using objectness detection
摘要
Abstract
To solve the tracking drift problem caused by the low discrimination of object appearance information in complex environment,the paper proposes an object tracking algorithm using objectness detection.First,the algorithm obtains the preliminary object prediction state with kernelized correlation filters.Then,according to the objectness detection principle of the proposal bounding box,it generates the original proposal bounding box set with the consideration of the scale and aspect ratio,and further gets optimized sets with the refined selection criterion.By introducing motion continuity,the prediction location and scale based on the proposal bounding box are calculated,and then the final optimum object state estimation is acquired comprehensively.Finally,taking into account the occlusion influence judge of target appearance at the current frame,the corresponding template updating scheme is given.Experimental results demonstrate that the novel algorithm achieves robust tracking performance in various typical testing scenarios.关键词
目标跟踪/相关滤波/建议边界框/更新策略Key words
object tracking/correlation filters/proposal bounding box/updating scheme分类
信息技术与安全科学引用本文复制引用
胡秀华,郭雷,李晖晖..一种利用物体性检测的目标跟踪算法[J].西安电子科技大学学报（自然科学版）,2017,44(4):86-94,111,10.基金项目
国家自然科学基金资助项目(61273362) （61273362）
国家自然科学基金重点资助项目(61333017) （61333017）
