基于局部行颜色自相似性特征的行人检测方法  

A Method of Pedestrian Detection Based on the Local Row Color Self-similarity

作　　者：翟芬[1] 蔡烜[2] 李一蒙[2] 冯瑞[3] 

机构地区：[1]复旦大学计算机科学技术学院,上海视频技术与系统工程研究中心 [2]公安部第三研究所 [3]复旦大学

出　　处：《微型电脑应用》2015年第4期4-7,共4页Microcomputer Applications

基　　金：国家科技支撑计划(2013BAH09F01);上海市科委科技创新行动计划(14511106900)

摘　　要：针对计算机视觉领域的行人检测问题,提出一种基于局部行颜色自相似性特征,该特征可表征为在HSV空间,图像水平方向非重叠对称块颜色直方图的距离信息,结合多层次导向边缘能量特征形成图像的融合特征,利用交叉核支持向量机进行分类。与主流用于行人检测的HOG+SVM方法相比,其特征维数低,在保证检测精度的同时,大幅提高了算法效率。实验结果验证了该算法的有效性。For pedestrian detection problems in computer vision, this paper proposes a feature based on the local row color self-similarity. In HSV space, this feature represents the color histogram distance of the symmetric non-overlapping blocks in the horizontal direction. It combined Multi-Level Oriented Edge Energy Features with this feature to obtain fusional features, and used Histogram Intersection Kernel Support Vector Machine to classify. Compared to the method of mainstream HOG＋SVM, the dimension of this feature is lower. While guaranteeing the detection accuracy, the efficiency of this method is improved mostly. Experiment results validate the effectiveness of the proposed approach.

关 键 词：行人检测 局部行颜色自相似性 多层次导向边缘能量特征 交叉核支持向量机 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]