宋怀波,韩梦璇,王云飞,宋磊,陈春堃.基于人体姿态估计与场景交互的果园喷施行为检测方法[J].农业机械学报,2023,54(2):63-72.
SONG Huaibo,HAN Mengxuan,WANG Yunfei,SONG Lei,CHEN Chunkun.Monitoring of Spraying Behavior in Orchard Based on Interaction of Human Posture Estimation and Scenes[J].Transactions of the Chinese Society for Agricultural Machinery,2023,54(2):63-72.
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基于人体姿态估计与场景交互的果园喷施行为检测方法   [下载全文]
Monitoring of Spraying Behavior in Orchard Based on Interaction of Human Posture Estimation and Scenes   [Download Pdf][in English]
投稿时间:2022-03-30  
DOI:10.6041/j.issn.1000-1298.2023.02.006
中文关键词:  果品溯源  喷施行为检测  场景交互  姿态估计  行为识别
基金项目:国家重点研发计划项目(2019YFD1002401)
作者单位
宋怀波 西北农林科技大学 
韩梦璇 西北农林科技大学 
王云飞 西北农林科技大学 
宋磊 西北农林科技大学 
陈春堃 西北农林科技大学 
中文摘要:果园农药施用情况是果品质量安全的重要检验标准,农药喷施行为的可靠记录是果品溯源体系的重要环节。针对我国目前常见的果品种植专业合作社中难以确切掌握农药施用真实情况的问题,本研究提出了一种基于人体姿态估计与场景交互的果园背负式喷施行为检测方法。首先采用微调后的YOLO v5模型完成背负式喷雾器与果树目标的精确检测,提取场景交互特征;之后采用OpenPose模型识别喷施人员姿态及动作信息,提取人体姿态特征;最后对上述特征分别进行距离和角度计算,将其融合为11244组特征向量并使用优化后的支持向量机(Support vector machine, SVM)进行训练,完成果园喷施行为的准确检测。为了验证算法的有效性,对包含不同光照、不同距离、不同人数和不同遮挡程度等的92段视频进行了测试。试验结果表明,该算法的准确度为85.66%,平均绝对误差为42.53%,均方根误差为44.59%,预测标准偏差为44.34%,以及性能偏差比为1.56。同时,本研究对不同光照、遮挡、距离变化和多人中单人喷施情况下的果园喷施行为识别的有效性进行了分析。试验结果表明,将该模型用于果园喷施行为的检测是可行的,本研究可为果品溯源体系中果园管理环节的规范化和可信度提供技术参考。
SONG Huaibo  HAN Mengxuan  WANG Yunfei  SONG Lei  CHEN Chunkun
Northwest A&F University
Key Words:fruit traceability  monitoring of spraying behavior  scene interaction  posture estimation  behavior recognition
Abstract:Pesticide spraying in orchard is an important inspection content of fruit quality and safety, and the reliable record of pesticide spraying behavior is an important part of fruit traceability system. Aiming at solving the problem that it was difficult to accurately grasp the real situation of pesticide application in the farmer professional cooperatives during the fruit planting in China, monitoring of the spraying behavior in orchard based on the interaction of human posture estimation and scenes was proposed. Firstly, the fine tuned YOLO v5 model was used to complete the precise detection of sprayers and fruit tree targets, and the features of scene interaction were extracted. Then, the OpenPose model was used to recognize human skeleton and extract human posture features. Finally, the distance and angle of the above features were calculated respectively, and fused into 11244 sets of feature vectors, which were trained by the SVM model to complete the detection of orchard spraying behavior. In order to verify the effectiveness of the algorithm, totally 92 videos with different illuminations, different distances, different numbers of people and different occlusion degrees were tested. The results showed that the ACC of the algorithm was 85.66%, the MAE was 42.53%, the RMSE was 44.59%, the RMSEP was 44.34% and the RPD was 1.56. Simultaneously, the effectiveness of spraying behavior recognition in orchard was validated under different illuminations, occlusions, distance change and single spraying among multiple people. Experimental results showed that it was feasible to apply the model to the detection of orchard spraying behavior. The research result could provide technical reference for the standardization and reliability of orchard management in the fruit traceability system.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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