Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF

IF 2.2 2区 农林科学 Q2 AGRICULTURAL ENGINEERING International Journal of Agricultural and Biological Engineering Pub Date : 2023-01-01 DOI:10.25165/j.ijabe.20231603.6930
Chengqi Liu, Haijian Ye, Shuhan Lu, Zhan Tang, Zhao Bai, Lei Diao, Longhe Wang, Lin Li
{"title":"Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF","authors":"Chengqi Liu, Haijian Ye, Shuhan Lu, Zhan Tang, Zhao Bai, Lei Diao, Longhe Wang, Lin Li","doi":"10.25165/j.ijabe.20231603.6930","DOIUrl":null,"url":null,"abstract":"The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs. Accordingly, this study proposed a novel approach for the skeleton extraction and pose estimation of piglets. First, an improved Zhang-Suen (ZS) thinning algorithm based on morphology was used to establish the chain code mechanism of the burr and the redundant information deletion templates to achieve a single-pixel width extraction of pig skeletons. Then, body nodes were extracted on the basis of the improved DeepLabCut (DLC) algorithm, and a part affinity field (PAF) was added to realize the connection of body nodes, and consequently, construct a database of pig behavior and postures. Finally, a support vector machine was used for pose matching to recognize the main behavior of piglets. In this study, 14 000 images of piglets with different types of behavior were used in posture recognition experiments. Results showed that the improved algorithm based on ZS-DLC-PAF achieved the best thinning rate compared with those of distance transformation, medial axis transformation, morphology refinement, and the traditional ZS algorithm. The node tracking accuracy reached 85.08%, and the pressure test could accurately detect up to 35 nodes of 5 pigs. The average accuracy of posture matching was 89.60%. This study not only realized the single-pixel extraction of piglets’ skeletons but also the connection among the different behavior body nodes of individual sows and multiple piglets. Furthermore, this study established a database of pig posture behavior, which provides a reference for studying animal behavior identification and classification and anomaly detection. Keywords: piglets, skeleton extraction, pose estimation, Zhang-Suen, DeepLabCut, Part affinity field DOI: 10.25165/j.ijabe.20231603.6930 Citation: Liu C Q, Ye H J, Lu S H, Tang Z, Bai Z, Diao L, et al. Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF. Int J Agric & Biol Eng, 2023; 16(3): 180–193.","PeriodicalId":13895,"journal":{"name":"International Journal of Agricultural and Biological Engineering","volume":null,"pages":null},"PeriodicalIF":2.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Agricultural and Biological Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25165/j.ijabe.20231603.6930","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0

Abstract

The accurate identification of various postures in the daily life of piglets that are directly reflected by their skeleton morphology is necessary to study the behavioral characteristics of pigs. Accordingly, this study proposed a novel approach for the skeleton extraction and pose estimation of piglets. First, an improved Zhang-Suen (ZS) thinning algorithm based on morphology was used to establish the chain code mechanism of the burr and the redundant information deletion templates to achieve a single-pixel width extraction of pig skeletons. Then, body nodes were extracted on the basis of the improved DeepLabCut (DLC) algorithm, and a part affinity field (PAF) was added to realize the connection of body nodes, and consequently, construct a database of pig behavior and postures. Finally, a support vector machine was used for pose matching to recognize the main behavior of piglets. In this study, 14 000 images of piglets with different types of behavior were used in posture recognition experiments. Results showed that the improved algorithm based on ZS-DLC-PAF achieved the best thinning rate compared with those of distance transformation, medial axis transformation, morphology refinement, and the traditional ZS algorithm. The node tracking accuracy reached 85.08%, and the pressure test could accurately detect up to 35 nodes of 5 pigs. The average accuracy of posture matching was 89.60%. This study not only realized the single-pixel extraction of piglets’ skeletons but also the connection among the different behavior body nodes of individual sows and multiple piglets. Furthermore, this study established a database of pig posture behavior, which provides a reference for studying animal behavior identification and classification and anomaly detection. Keywords: piglets, skeleton extraction, pose estimation, Zhang-Suen, DeepLabCut, Part affinity field DOI: 10.25165/j.ijabe.20231603.6930 Citation: Liu C Q, Ye H J, Lu S H, Tang Z, Bai Z, Diao L, et al. Skeleton extraction and pose estimation of piglets using ZS-DLC-PAF. Int J Agric & Biol Eng, 2023; 16(3): 180–193.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于ZS-DLC-PAF的仔猪骨骼提取与位姿估计
准确识别仔猪日常生活中由其骨骼形态直接反映的各种姿势,是研究猪的行为特征所必需的。因此,本研究提出了一种新的仔猪骨骼提取和姿态估计方法。首先,采用改进的基于形态学的张孙(Zhang-Suen, ZS)细化算法,建立毛刺和冗余信息删除模板的链编码机制,实现猪骨架的单像素宽度提取;然后,基于改进的DeepLabCut (DLC)算法提取身体节点,并加入部位亲和场(PAF)实现身体节点的连接,从而构建猪的行为和姿态数据库。最后,利用支持向量机进行姿态匹配,识别仔猪的主要行为。本研究采用14000张不同行为类型的仔猪图像进行姿势识别实验。结果表明,基于ZS- dlc - paf的改进算法比距离变换、中轴线变换、形态细化和传统ZS算法的细化率最好。节点跟踪精度达到85.08%,压力测试最多可准确检测5头猪的35个节点。平均姿势匹配正确率为89.60%。本研究不仅实现了仔猪骨骼的单像素提取,而且实现了单头母猪和多头仔猪不同行为体节点之间的连接。此外,本研究建立了猪的姿势行为数据库,为研究动物行为识别分类和异常检测提供参考。关键词:仔猪,骨骼提取,姿态估计,zhangsuen, DeepLabCut,零件亲和场DOI: 10.25165/ j.j ijabe.20231603.6930引用本文:刘春青,叶海军,卢树华,唐志,白志,雕玲,等。基于ZS-DLC-PAF的仔猪骨骼提取与位姿估计。农业与生物工程学报,2023;16(3): 180 - 193。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
4.30
自引率
12.50%
发文量
88
审稿时长
24 weeks
期刊介绍: International Journal of Agricultural and Biological Engineering (IJABE, https://www.ijabe.org) is a peer reviewed open access international journal. IJABE, started in 2008, is a joint publication co-sponsored by US-based Association of Agricultural, Biological and Food Engineers (AOCABFE) and China-based Chinese Society of Agricultural Engineering (CSAE). The ISSN 1934-6344 and eISSN 1934-6352 numbers for both print and online IJABE have been registered in US. Now, Int. J. Agric. & Biol. Eng (IJABE) is published in both online and print version by Chinese Academy of Agricultural Engineering.
期刊最新文献
Effects of spray adjuvants and operation modes on droplet deposition and elm aphid control using an unmanned aerial vehicle Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry Design and test of the bilateral throwing soil-covering device for straw mulching machine in orchards Detection of the foreign object positions in agricultural soils using Mask-RCNN Separation and mechanical properties of residual film and soil
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1