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Real-time 3d arm pose estimation from monocular video for enhanced HCI

Published: 31 October 2008 Publication History

Abstract

In this paper an approach for 3D arm pose estimation from a monocular video is presented. Our proposal has been designed to provide real-time and realistic reconstruction of the user motion, as required by advanced Human Computer Interaction (HCI) applications. Both a 2D arm tracking and a 3D arm pose estimation algorithm are introduced and discussed. Tracking exploits fast and robust segmentation of the arm silhouette together with detection and tracking of skin colored regions. 3D pose estimation relies on a stick-figure arm model and the Analysis-by-Synthesis approach, but achieves real-time performance using geometrical constraints on tracking results to reduce the search space cardinality. Experiments on the animation of 3D avatars using off-the-shelf hardware demonstrate the effectiveness and real-time performance of our proposal.

References

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Cited By

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  • (2024)Light-Adaptive Human Body Key Point Detection Algorithm Based on Multi-Source Information FusionSensors10.3390/s2410302124:10(3021)Online publication date: 10-May-2024
  • (2023)A graph-based approach can improve keypoint detection of complex poses: a proof-of-concept on injury occurrences in alpine ski racingScientific Reports10.1038/s41598-023-47875-213:1Online publication date: 5-Dec-2023
  • (2021)A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical ExerciseSensors10.3390/s2118599621:18(5996)Online publication date: 7-Sep-2021
  • Show More Cited By

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cover image ACM Conferences
VNBA '08: Proceedings of the 1st ACM workshop on Vision networks for behavior analysis
October 2008
116 pages
ISBN:9781605583136
DOI:10.1145/1461893
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 31 October 2008

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Author Tags

  1. 3d arm pose estimation
  2. human computer interaction

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MM08: ACM Multimedia Conference 2008
October 31, 2008
British Columbia, Vancouver, Canada

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Cited By

View all
  • (2024)Light-Adaptive Human Body Key Point Detection Algorithm Based on Multi-Source Information FusionSensors10.3390/s2410302124:10(3021)Online publication date: 10-May-2024
  • (2023)A graph-based approach can improve keypoint detection of complex poses: a proof-of-concept on injury occurrences in alpine ski racingScientific Reports10.1038/s41598-023-47875-213:1Online publication date: 5-Dec-2023
  • (2021)A Systematic Review of the Application of Camera-Based Human Pose Estimation in the Field of Sport and Physical ExerciseSensors10.3390/s2118599621:18(5996)Online publication date: 7-Sep-2021
  • (2016)Arm Poses Modeling for Pedestrians with Motion PriorJournal of Signal Processing Systems10.1007/s11265-015-1049-684:2(237-249)Online publication date: 1-Aug-2016
  • (2015)Human arm pose modeling with learned features using joint convolutional neural network2015 14th IAPR International Conference on Machine Vision Applications (MVA)10.1109/MVA.2015.7153213(398-401)Online publication date: May-2015
  • (2012)Human sign recognition for robot manipulationProceedings of the 4th Mexican conference on Pattern Recognition10.1007/978-3-642-31149-9_11(107-116)Online publication date: 27-Jun-2012
  • (2010)Real time multiple people tracking and pose estimationProceedings of the 1st ACM international workshop on Multimodal pervasive video analysis10.1145/1878039.1878042(5-10)Online publication date: 29-Oct-2010

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