摘要
为了更好地了解豪猪的习性,提高豪猪人工养殖技术水平,本文设计了基于一种视频图像分析的圈养豪猪检测及基本行为识别方案。首先通过混合高斯模型背景建模法,对圈养豪猪养殖环境进行背景建模,标记出场景中的豪猪及其他运动物体轮廓,采用分类算法对识别出的轮廓进行分类,对豪猪的识别准确率达到86.34%;为了进一步提高准确率,引入图像局部特征ORB关键点作为分类属性,使豪猪的识别准确率提升到93.23%;在此基础上,以饲养池结构及豪猪活动实际情况为判断依据建立圈养豪猪行为识别模型,实现了对豪猪静息、进食、饮水、排泄、啃咬铁门及水槽等7种基本行为的识别。
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.
出处
《福建农业学报》
CAS
北大核心
2017年第9期1021-1025,共5页
Fujian Journal of Agricultural Sciences
基金
广东省科技计划项目(2012A020602043)
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
captive-farmed porcupine
mixed gaussian model
background modeling
ORB detection
support vector machines
data mining
