摘要
提出了一种通过综合利用表观和运动模式从视频中检测轮椅（包括坐轮椅的人）的方法。该方法首先使用两种特征描述轮椅的表观特性，并结合利用基于统计学习得到的分类器快速地排除非目标区域。针对由于直立行人和坐在轮椅人之间的表观相似性，轮椅检测易受直立行人干扰的情况，进一步使用运动信息来区分轮椅和正常行人，降低了虚警。在收集的数据上测试了所提方法的性能，实验结果表明提出的方法能够以接近实时的速度进行检测，并且能够有效地降低正常行人的干扰。
This paper proposes a novel method to detect wheelchairs in video using the combination of appearance and motion pattern. An appearance based detector is used to detect objects frame by frame, where a cascaded detector is designed using the Haar-like feature and the HOG （histograms of oriented gradients） feature. A motion based classifier is proposed further to distinguish appearance-similar wheelchairs and pedestrians, which, usually impedes performance of appearance based detectors. The accuracy and the efficiency of the proposed method were validated by extensive experiments.
出处
《高技术通讯》
CAS
CSCD
北大核心
2012年第2期153-158,共6页
Chinese High Technology Letters
基金
973计划（2007CB311004）资助项目.
