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

International Journal of Agricultural and Biological Engineering 2023年第3期16卷 180-193,F0004页

作者： Chengqi Liu Haijian Ye Shuhan Lu Zhan Tang Zhao Bai Lei Diao Longhe Wang Lin Li College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China School of Information University of MichiganAnn Arbor 48109USA National Research Facility for Phenotypic and Genotypic Analysis of Model Animals(Beijing) Beijing 100083China

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 ***,this study proposed a novel approach for the skeleton extraction and pose estimation of ***,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 ***,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 ***,a support vector machine was used for pose matching to recognize the main behavior of *** this study,14000 images of piglets with different types of behavior were used in posture recognition *** 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 *** node tracking accuracy reached 85.08%,and the pressure test could accurately detect up to 35 nodes of 5 *** 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 ***,this study established a database of pig posture behavior,which provides a reference for studying animal behavior identification and classification and anomaly detection.

关键词： piglets skeleton extraction pose estimation Zhang-Suen DeepLabCut Part affinity field

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skeleton extraction of boiler flame images based on mathematical morphology

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Journal of Southeast University(English Edition) 2003年第4期19卷 352-354页

作者：华彦平于向军吕震中东南大学动力工程系南京210096

In this paper, a method and algorithm of skeleton extraction based on binary mathematical morphology is presented. Sequential structuring elements (SEs) is also studied, which is the key problem of skeleton extraction. The examples of boiler flame image processing show that the detected skeletons can present the geometric shape of flame images well.

关键词： mathematical morphology flame image skeleton extraction

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On skeleton extraction Algorithm for Path Planning of Mobile Robots in Complex Planar Maps

On Skeleton Extraction Algorithm for Path Planning of Mobile...

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第二十九届中国控制会议

作者： LI Ming,WANG Jun,ZHU Meiqiang School of Information and Electrical Engineering,China University of Mining and Technology,Xuzhou 221008,P.R.China

For path planning in complex maps,this paper proposes skeleton extraction algorithm to realize initial path generation in two-dimensional *** extraction algorithm can reduce the dimension of two-dimension maps,and transform it to one-dimension feasible path map by extracting skeleton of planar *** long as a path connecting starting point and target point is found based on the skeleton,path planning and optimization can be achieved in complex ***,skeleton extraction can be applied to path planning of mobile robots in complex planar *** skeleton extraction algorithm is simulated and its efficiency is validated in simulation condition.

关键词： skeleton extraction Path Planning Global Map Real-Time Path Planning

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A novel method for extracting skeleton of fruit treefrom 3D point clouds

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International Journal of Modeling, Simulation, and Scientific Computing 2020年第6期11卷 78-89页

作者： Shenglian Lu Guo Li Jian Wang College of Computer Science and Information Technology Guangxi Normal University Guilin 541004P.R.China Guangxi Key Lab of Multi-Source Information Mining and Security No.15 Yucai Road Guilin 541004P.R.China Center of Information Technology Beijing Municipal Bureau of Agriculture and Rural Affairs No.6 Yumin Middle Rood Beijing 100029P.R.China

Tree skeleton could be useful to agronomy researchers because the skeleton describes the shape and topological structure of a *** phenomenon of organs’mutual occlusion in fruit tree canopy is usually very serious,this should result in a large amount of data missing in directed laser scanning 3D point clouds from a fruit ***,traditional approaches can be ineffective and problematic in extracting the tree skeleton correctly when the tree point clouds contain occlusions and missing *** overcome this limitation,we present a method for accurate and fast extracting the skeleton of fruit tree from laser scanner measured 3D point *** proposed method selects the start point and endpoint of a branch from the point clouds by user’s manual interaction,then a backward searching is used to find a path from the 3D point cloud with a radius parameter as a *** experimental results in several kinds of fruit trees demonstrate that our method can extract the skeleton of a leafy fruit tree with highly accuracy.

关键词： skeleton extraction fruit tree 3D point cloud modeling plant structure

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SlowFast Based Real-Time Human Motion Recognition with Action Localization

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Computer Systems Science & Engineering 2023年第11期47卷 2135-2152页

作者： Gyu-Il Kim Hyun Yoo Kyungyong Chung Department of Computer Science Kyonggi UniversitySuwon16227Korea Contents Convergence Software Research Institute Kyonggi UniversitySuwon16227Korea Division of AI Computer Science and Engineering Kyonggi UniversitySuwon16227Korea

Artificial intelligence is increasingly being applied in the field of video analysis,particularly in the area of public safety where video surveillance equipment such as closed-circuit television(CCTV)is used and automated analysis of video information is ***,various issues such as data size limitations and low processing speeds make real-time extraction of video data *** analysis technology applies object classification,detection,and relationship analysis to continuous 2D frame data,and the various meanings within the video are thus analyzed based on the extracted basic *** recognition is key in this *** recognition is a challenging field that analyzes human body movements,requiring the interpretation of complex movements of human joints and the relationships between various *** deep learning-based human skeleton detection algorithm is a representative motion recognition ***,motion analysis models such as the SlowFast network algorithm,have also been developed with excellent ***,these models do not operate properly in most wide-angle video environments outdoors,displaying low response speed,as expected from motion classification extraction in environments associated with high-resolution *** proposed method achieves high level of extraction and accuracy by improving SlowFast’s input data preprocessing and data structure *** input data are preprocessed through object tracking and background removal using YOLO and DeepSORT.A higher performance than that of a single model is achieved by improving the existing SlowFast’s data structure into a frame unit *** on the confusion matrix,accuracies of 70.16%and 70.74%were obtained for the existing SlowFast and proposed model,respectively,indicating a 0.58%increase in *** detection,based on behavioral classification,the existing SlowFast detected 2,341,164 cases,whereas the proposed model detected 3,11

关键词： Artificial intelligence convolutional neural network video analysis human action recognition skeleton extraction

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