红外技术2017，Vol.39Issue(11)：1038-1044,1053,8.
复杂背景下红外人体目标检测算法研究
Research on Infrared Human Detection from Complex Backgrounds
马也 1常青 1胡谋法1
作者信息
- 1. 国防科技大学 电子科学与工程学院 ATR 重点实验室,湖南 长沙 410073
- 折叠
摘要
Abstract
Infrared images have disadvantages such as low signal-to-noise ratio and contrast, a lack of color texture information, and a halo effect around target and blurry edges. These factors pose challenges for detecting humans in infrared images. This study focuses on human detection technology used for infrared image sequences in complicated environments. Specifically, we use a background subtraction method to segment a human-body target based on a modified Gaussian mixture model. First, we use multiple Gaussian processes to simulate the complex changes in the background with the appropriate weight values. These processes also update the number, weight values, and learning rate of the Gaussian model. We then use the fusion of the accumulated oriented edges and a histogram of oriented gradient characteristics to describe the region of interest. Finally, we employ a support vector machine to classify the human targets precisely. Experiments show that the algorithm can detect human targets accurately in complex backgrounds and that it generates good results on multiple objects, those near in distance, and even some of having adhesion multiple objects, near distance, and even some of the adhesion.关键词
红外图像/人体检测/混合高斯模型/边缘方向累加和/梯度方向直方图/支持向量机Key words
infrared image/human detection/GMM/AOE/HOG/SVM分类
信息技术与安全科学引用本文复制引用
马也,常青,胡谋法..复杂背景下红外人体目标检测算法研究[J].红外技术,2017,39(11):1038-1044,1053,8.
