改进的红外图像行人检测和交叠率算法

行人越界入侵报警是十分普遍的应用场景,尤其是在安保领域.本文设计了一种改进的红外图像行人检测和交叠率算法,两者结合可以实现对行人的越界报警.本方法主要由三部分组成:红外图像行人检测算法、目标分类算法、交叠率算法与报警逻辑.红外图像是为了尽量克服环境影响,并且在夜间也具有良好的显示与图像采集功能;行人检测是通过YOLOv3算法和基于方向梯度直方图(HOG)特征的多层感知器(MLP)二分类来实现;报警算法与逻辑是计算目标的候选框与报警区域的交叠率,再进行逻辑判断.实验表明,本方法准确性高,报警准确率可达91%,有良好的应用价值.

Improved Algorithm for Infrared Pedestrian Detection and Overlap Rate

In this study, we proposed an improved method of infrared pedestrian detection and overlap rate, which could be used for positioning and abnormal alarm, especially in the security industry. The method is consisted of three steps: 1) infrared pedestrian detection algorithm; 2) classification algorithm; 3) overlap rate algorithm and the logic of alarm. Infrared sensors could collect high quality image data at night, and overcome environmental interference as much as possible. Pedestrian detection was designed by YOLOv3 algorithm and Multi-Layer Perception (MLP) based on Histogram of Oriented Gradient (HOG) features. The abnormal alarms were proposed by calculating overlap rate between pedestrian detection bound and ground truth bound, and then making logical judgment. The experiments evidenced the benefits of proposed approach, which could effectively improve pedestrian detection performance and abnormal alarm accuracy (over 91%).