摘要
针对灾难中被困者的识别问题,提出了一种遮挡状态下的非完整人体特征检测方法;基于头部、腿部等可能暴露在外的人体特征,先构造相交检测窗口,重新检测目标图像块内的方向梯度直方图(HOG)特征,并结合基于子单元插值的方法计算块内特征,从而实现了基于优化HOG特征的非完整人体特征检测;实验结果表明,该优化HOG特征计算后的非完整人体检测方法可显著提高人体检测的检测速度和准确性,降低误检率。
A method of incomplete human feature detection under occlusion is proposed to identify trapped persons in disasters.In light of exposure of human characteristics such as the head and legs,the intersection detection window is constructed,and the features of histogram of oriented gradient(HOG)within the targeted image block are redetected.The intra-block features are calculated by combining the sub-unit interpolation method,so that the incomplete human feature detection is feasible on the basis of optimized HOG features.Experimental results show that the optimized human body detection method based on HOG feature calculation can significantly improve the detection speed and accuracy of human detection,and reduce the false detection rate.
作者
李闯
陈张平
王坚
张波涛
Li Chuang;Chen Zhangping;Wang Jian;Zhang Botao(School of automation,Hangzhou Dianzi University,Hangzhou 310018,China)
出处
《计算机测量与控制》
2018年第11期238-242,共5页
Computer Measurement &Control
基金
国家级大学生创新训练项目(201610336027)
国家自然科学基金项目(61611530709)
关键词
搜索与救援
人体检测
特征组合
HOG特征
search and rescue
human detection
combination of features
HOG feature
