智能系统学报2016，Vol.11Issue(5)：619-626,8.DOI:10.11992/tis.201603050
一种鲁棒的Multi-Egocentric视频中的多目标检测及匹配算法
A robust multi-object detection and matching algorithm for multi-egocentric videos
摘要
Abstract
In this paper, a robust multi⁃object detection and matching algorithm for a multi⁃egocentric video is pro⁃posed by considering the characteristics of multi⁃egocentric videos, for example, sudden changes in background, and variable target scales and viewpoints. First, a multi⁃target detection model based on a boosting method is con⁃structed, to roughly detect any salient objects in the video frames. Then an optimization algorithm based on local similarity is proposed for optimizing the salient⁃object area and improving the accuracy of salient⁃object detection and localization. Finally, a SVM classifier based on HOG features is trained to realize multi⁃target matching in multi⁃egocentric videos. Experiments using Scene Party datasets show the effectiveness of the proposed method.关键词
Multi-Egocentric视频/多目标检测/多目标匹配Key words
multi-egocentric video/multi-object detection/multi-object matching分类
信息技术与安全科学引用本文复制引用
李龙,尹辉,许宏丽,欧伟奇..一种鲁棒的Multi-Egocentric视频中的多目标检测及匹配算法[J].智能系统学报,2016,11(5):619-626,8.基金项目
国家自然科学基金项目（61472029，61473031）． （）
