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
刘琼;陈雯柏
【期刊名称】《计算机应用研究》 【年(卷),期】2016(000)001
【摘要】常规的行人目标检测方法往往以底层特征为基础,采用密集窗口扫描的分类检测模式,其计算资源开销大而难以满足快速性要求。针对此问题,研究了一种新的行人目标快速检测方法。引入视觉选择性注意计算进行目标候选区域定位,通过提取候选区域的积分有向梯度直方图 IHOG(integrated histogram of oriented gradi-ent)特征和局部二值模式 LBP(local binary pattern)特征以形成组合优势,通过级联支持向量分类方式对区域内容进行分级检测,实现了快速、可靠的行人目标检测。DET(detection error tradeoff)曲线和算法运行时间表明,相比 Dalal 等人的方法,本方法可在保证检测率稳定的前提下,缩短五倍的检测时间,具有更好的工程应用性。%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