WEKO3
アイテム
Development of a Real-Time Multi-Person 3D Keypoint Detection System Using Stereoscopic Cameras and RTMPose
http://hdl.handle.net/10458/0002001862
http://hdl.handle.net/10458/0002001862565de014-b7af-4eb1-9331-e3a39c1679b8
| 名前 / ファイル | ライセンス | アクション |
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| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||||||
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| 公開日 | 2025-10-24 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Development of a Real-Time Multi-Person 3D Keypoint Detection System Using Stereoscopic Cameras and RTMPose | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 言語 | eng | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| キーワード | computer vision | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | multi-person 3D keypoint detection | |||||||||||||||
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| 言語 | en | |||||||||||||||
| キーワード | real-time biomechanical analysis | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| キーワード | RTMpose | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ | journal article | |||||||||||||||
| アクセス権 | ||||||||||||||||
| アクセス権 | open access | |||||||||||||||
| 著者 |
Soesilo, Taufik Hidayat
× Soesilo, Taufik Hidayat
× Gunaratne, Praveen Nuwantha
× 田村, 宏樹
WEKO
7150
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| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | The feature offers a way of tracking the movement patterns of many people at once, and is critical in occupational health, sports performance, and team-based work settings. The selected traditional biomechanical analysis systems, in turn, are largely considered in detecting single person movement, which weakens their applicability to movement analysis that involves interacting with multiple people. In this paper we consider a real time multi-person detection and analysis system using stereoscopic cameras and RTMPose, a novel high real-time pose estimation framework. RTMPose offers real time analysis of 2D key points for the individuals and this data is later augmented with depth data coming from stereoscopic imaging to give 3D skeletal data. The benefit of employing RTMPose is that the system is able to perform accurate and fast multiple persons tracking despite present occlusion scenarios. Consequently, the system overcomes the drawbacks of prior methods, including reliance on wearable devices and unsuitability for out-of-door environments, by employing stereoscopic cameras and RTMPose with low-latency and high-accurate inference. Experimental results demonstrate the system’s ability to provide detailed real-time analysis of posture and movement for multiple individuals in diverse scenarios. This research highlights the potential of RTMPose-powered systems to advance multi-person biomechanical analysis for applications ranging from workplace monitoring to sports performance assessment. | |||||||||||||||
| 言語 | en | |||||||||||||||
| 書誌情報 |
en : Proceedings of International Conference on Artificial Life and Robotics ja : 人工生命とロボットに関する国際会議予稿集 巻 30, p. 593-596, 発行日 2025-02-13 |
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| 出版者 | ALife Robotics | |||||||||||||||
| 言語 | en | |||||||||||||||
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| 収録物識別子タイプ | EISSN | |||||||||||||||
| 収録物識別子 | 24359157 | |||||||||||||||
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| 関連タイプ | isVersionOf | |||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||
| 関連識別子 | https://doi.org/10.5954/icarob.2025.os21-5 | |||||||||||||||
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| 出版タイプ | VoR | |||||||||||||||
