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human Pose Estimation and object interaction for Sports Behaviour

Computers, Materials & Continua 2022年第7期72卷 1-18页

作者： Ayesha Arif Yazeed Yasin Ghadi Mohammed Alarfaj Ahmad Jalal Shaharyar Kamal Dong-Seong Kim Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science and Software Engineering Al Ain UniversityAl Ain15551UAE Department of Electrical Engineering College of EngineeringKing Faisal UniversityAl-AhsaSaudi Arabia Department of IT Convergence Engineering Kumoh National Institute of TechnologyGumiKorea

In the new era of technology,daily human activities are becoming more challenging in terms of monitoring complex scenes and *** understand the scenes and activities from human life logs,human-object interaction(HOI)is important in terms of visual relationship detection and human pose *** understanding and interaction recognition between human and object along with the pose estimation and interaction modeling have been *** existing algorithms and feature extraction procedures are complicated including accurate detection of rare human postures,occluded regions,and unsatisfactory detection of objects,especially small-sized *** existing HOI detection techniques are instancecentric(object-based)where interaction is predicted between all the *** estimation depends on appearance features and spatial ***,we propose a novel approach to demonstrate that the appearance features alone are not sufficient to predict the ***,we detect the human body parts by using the Gaussian Matric Model(GMM)followed by object detection using *** predict the interaction points which directly classify the interaction and pair them with densely predicted HOI vectors by using the interaction *** interactions are linked with the human and object to predict the *** experiments have been performed on two benchmark HOI datasets demonstrating the proposed approach.

关键词： human object interaction human pose estimation object detection sports estimation sports prediction

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