Scale-adaptive compressive tracking with feature integration
作者: Wei LiuJicheng LiXiao ChenShuxin Li
作者单位: 1National University of Defense Technology
刊名: Journal of Electronic Imaging, 2016, Vol.25 (3), pp.033018-033018
来源数据库: SPIE-the International Society for Optical Engineering
DOI: 10.1117/1.JEI.25.3.033018
关键词: tracking-by-detectioncompressive trackingscale estimationfeature integration
原始语种摘要: Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed...
全文获取路径: SPIE 

  • integration 集成
  • adaptive 适应的
  • tracking 跟踪
  • feature 结构元件
  • illumination 光照强度
  • tracker 跟踪装置
  • robustness 坚固性
  • projection 投射
  • classifier 分级机
  • demonstrate 说明