计算机应用研究Issue(1)：281-285,5.DOI:10.3969/j.issn.1001-3695.2016.01.065
基于视觉选择性注意与IHOG-LBP 特征组合的行人目标快速检测
Fast pedestrian detection method based on combinatory features IHOG-LBP and visual selective attention computation
摘要
Abstract
Traditional pedestrian detection methods adopted intensive window scanning and underlying primitive features,the cost of computing resources was very large,and detection speed could not well adapt the continuously developing application re-quirements.This paper developed a new method to solve this problem based on visual selective attention computation.Firstly,it computed visual selective attention to position possible target regions as candidate ones.Then,it extracted IHOG (integrated histogram of oriented gradient)features and LBP(local binary pattern)features to form combinatory features of candidate re-gions.Finally,it trained a hierarchical three level SVM classifiers with different feature dimensions and increasingly precision in a “cascade”framework to detect effectively and discard some non-pedestrian background areas rapidly.Therefore,the pro-posed method realized high speed and confidence detection of pedestrian target area.DET(detection error tradeoff)curve and the running time of algorithms show that,compared to the Dalal et al.method,the proposed method can achieve stable true de-tection rate and shorten the detection time of 5 times,thus with better engineering applicability.关键词
行人检测/视觉选择性注意/积分有向梯度直方图/局部二值模式/级联分类/支持向量机Key words
pedestrian detection/visual selective attention/integrated histogram of orientation gradient/local binary pat-tern/cascaded classification/support vector machine分类
信息技术与安全科学引用本文复制引用
刘琼,陈雯柏..基于视觉选择性注意与IHOG-LBP 特征组合的行人目标快速检测[J].计算机应用研究,2016,(1):281-285,5.基金项目
北京市教育委员会科技发展计划面上项目（KM201411232008）；北京市属高等学校青年拔尖人才培育计划资助项目 （）
