一种基于低分辨红外传感器的动作识别方法  

Activity Recognition Approach Using a Low-Resolution Infrared Sensor

作　　者：张昱彤 翟旭平[1] 汪静[1] ZHANG Yutong;ZHAI Xuping;WANG Jing(Key Laboratory of Specialty Fiber Optics and Optical Access Networks,Shanghai University,Shanghai 200444,China)

机构地区：[1]上海大学,特种光纤与光接入网重点实验室,上海200444

出　　处：《红外技术》2022年第1期47-53,共7页Infrared Technology

摘　　要：如今,世界各国人口老龄化问题日益严重,为了避免独居老人发生意外,老人日常动作监测和识别算法成为了研究热点。本文设计了一种基于低分辨红外传感器的动作识别方法,通过红外传感器采集探测区的温度分布数据,对温度分布数据进行处理,从时间、温度、形变和轨迹4个方面提取多个特征,最后通过K近邻算法对"行走"、"弯腰"、"坐下"、"站起"和"摔倒"5种动作进行分类。实验结果表明平均识别准确率可达到97%,其中摔倒动作的识别准确率为100%。The worldwide problem of population aging is becoming increasingly critical.To avoid accidents involving the elderly living alone,the study of the daily activities of the elderly using recognition and monitoring algorithms has become a research hotspot.This paper proposes an action recognition approach using a low-resolution infrared sensor.The proposed approach uses an infrared sensor to collect temperature distribution data in the detection area,and then processes the temperature distribution data,extracting multiple features in the four dimensions of time,temperature,deformation,and trajectory.Finally,the K-nearest neighbors algorithm is used to identify the five poses of“walking,”“bending,”“sitting,”“standing,”and“falling.”Experimental results demonstrate that the average accuracy can reach 97%and that the accuracy for falling is 100%.

关 键 词：动作识别 特征提取 低分辨率红外传感器 K近邻算法 

分 类 号：TP319.4[自动化与计算机技术—计算机软件与理论]