摘要
在研究了人类视觉系统处理机制的基础上,首先利用方向梯度描述符(HOG)建立了图像的鲁棒表示;然后,根据人类视觉系统的并行处理机制和仿生信息学理论,提出了基于HOG+SVM的人体行为仿生识别与分类方法。利用针对识别与分类方法的评价指标对本文方法进行了评价,最后,与目前常用方法进行了比较,结果表明,在针对静态图像中人体行为的分类与识别效果方面,本文方法对差别较大的行为的识别效果好于常用方法,对相似行为的识别效果还有待于进一步提高。
The robust representation of image is established by Histogram of Oriented Gradient(HOG).According to the processing mechanism of human visual system and the theory of multidimensional space biomimetic informatics,a biomimetic classification and recognition method of human behavior are proposed,which is based on HOG+SVM.The method is evaluated and compared with other commonly used methods.Results show that,for the classification and recognition of human behavior in still image,the proposed methods have better performance in recognizing different kinds of behavior,but the performance in recognizing similar behaviors still needs improvement.
出处
《吉林大学学报（工学版）》
EI
CAS
CSCD
北大核心
2013年第S1期489-492,共4页
Journal of Jilin University:Engineering and Technology Edition
基金
国家自然科学基金项目(50635030)
关键词
人工智能
方向梯度描述符
支持向量机
人体行为
仿生识别
artificial intelligence
Histogram of Oriented Gradient(HOG),support vector machine(SVM)
human behavior
biomimetic recognition
