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SimpleDepthPose: fast and reliable human pose estimation with RGBD-images

  • In the rapidly advancing domain of computer vision, accurately estimating the poses of multiple individuals from various viewpoints remains a significant challenge, especially when reliability is a key requirement. This paper introduces a novel algorithm that excels in multi-view, multi-person pose estimation by incorporating depth information. An extensive evaluation demonstrates that the proposed algorithm not only generalizes well to unseen datasets, and shows a fast runtime performance, but also is adaptable to different keypoints. To support further research, all of the work is publicly accessible.

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Metadaten
Author:Daniel BermuthGND, Alexander PoeppelORCiDGND, Wolfgang ReifORCiDGND
URN:urn:nbn:de:bvb:384-opus4-1202938
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/120293
URL:https://arxiv.org/abs/2501.18478
Parent Title (English):arXiv
Publisher:arXiv
Type:Preprint
Language:English
Date of Publication (online):2025/03/13
Year of first Publication:2025
Publishing Institution:Universität Augsburg
Release Date:2025/03/14
Issue:arXiv:2501.18478
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Software & Systems Engineering
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Softwaretechnik / Lehrstuhl für Softwaretechnik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):License LogoCC-BY-SA 4.0: Creative Commons: Namensnennung - Weitergabe unter gleichen Bedingungen (mit Print on Demand)