福建农业学报2017，Vol.32Issue(9)：1021-1025,5.DOI:10.19303/j.issn.1008-0384.2017.09.018
基于机器视觉的圈养豪猪检测与基本行为识别方法研究
Video Monitoring Behaviors of Captive-farmed Porcupines
摘要
Abstract
To understand the living habits for remotely managing the breeding of captive-farmed porcupines,this study applied video to monitor and establish a recognition model with the aid of computation for the behaviors of the animals.Firstly,the mixed Gaussian background modeling was used to build a movement contour model of the porcupines in the pan.Using 3 chosen classifiers,the marked scenes of porcupine activities were categorized with an accuracy of 86.34 ％.Subsequently,ORB key points were introduced as an additional attribute for the classification which raised the accuracy to 93.23 ％.The resulting model could now recognize 7 basic behaviors,including resting,eating,drinking,excretion,and chewing an iron gate or a water trough,of porcupines in captivity.关键词
圈养豪猪/混合高斯模型/背景建模/ORB特征点检测/支持向量机/决策树Key words
captive-farmed porcupine/mixed gaussian model/background modeling/ORB detection/support vector machines/data mining分类
信息技术与安全科学引用本文复制引用
杨威,俞守华..基于机器视觉的圈养豪猪检测与基本行为识别方法研究[J].福建农业学报,2017,32(9):1021-1025,5.基金项目
广东省科技计划项目(2012A020602043) （2012A020602043）
