Hand pose estimation by combining fingertip tracking and articulated ICP
In this paper we present a model-based framework for hand pose estimation, which relies on the depth and color image sequence input. The proposed framework adopts a divide-and-conquer scheme, and combines fingertip tracking and articulated iterative closest point approach to restore the hand motion....
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/99271 http://hdl.handle.net/10220/12847 |
| _version_ | 1826122739417612288 |
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| author | Liang, Hui Yuan, Junsong Thalmann, Daniel |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Liang, Hui Yuan, Junsong Thalmann, Daniel |
| author_sort | Liang, Hui |
| collection | NTU |
| description | In this paper we present a model-based framework for hand pose estimation, which relies on the depth and color image sequence input. The proposed framework adopts a divide-and-conquer scheme, and combines fingertip tracking and articulated iterative closest point approach to restore the hand motion. The tracked fingertip positions are used to provide an initial estimation of the hand pose, and articulated ICP are adopted for further refinement. Experiments on both synthetic data and real-world sequences show the hand pose estimation scheme can accurately capture the natural hand motion. |
| first_indexed | 2024-10-01T05:53:25Z |
| format | Conference Paper |
| id | ntu-10356/99271 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:53:25Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/992712020-03-07T12:48:41Z Hand pose estimation by combining fingertip tracking and articulated ICP Liang, Hui Yuan, Junsong Thalmann, Daniel School of Electrical and Electronic Engineering International Conference on Virtual-Reality Continuum and its Applications in Industry (11th : 2012 : Singapore) DRNTU::Engineering::Electrical and electronic engineering In this paper we present a model-based framework for hand pose estimation, which relies on the depth and color image sequence input. The proposed framework adopts a divide-and-conquer scheme, and combines fingertip tracking and articulated iterative closest point approach to restore the hand motion. The tracked fingertip positions are used to provide an initial estimation of the hand pose, and articulated ICP are adopted for further refinement. Experiments on both synthetic data and real-world sequences show the hand pose estimation scheme can accurately capture the natural hand motion. 2013-08-02T03:23:09Z 2019-12-06T20:05:15Z 2013-08-02T03:23:09Z 2019-12-06T20:05:15Z 2012 2012 Conference Paper Liang, H., Yuan, J., & Thalmann, D. (2012). Hand pose estimation by combining fingertip tracking and articulated ICP. Proceedings of the 11th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry - VRCAI '12, 87-90. https://hdl.handle.net/10356/99271 http://hdl.handle.net/10220/12847 10.1145/2407516.2407543 en |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Liang, Hui Yuan, Junsong Thalmann, Daniel Hand pose estimation by combining fingertip tracking and articulated ICP |
| title | Hand pose estimation by combining fingertip tracking and articulated ICP |
| title_full | Hand pose estimation by combining fingertip tracking and articulated ICP |
| title_fullStr | Hand pose estimation by combining fingertip tracking and articulated ICP |
| title_full_unstemmed | Hand pose estimation by combining fingertip tracking and articulated ICP |
| title_short | Hand pose estimation by combining fingertip tracking and articulated ICP |
| title_sort | hand pose estimation by combining fingertip tracking and articulated icp |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/99271 http://hdl.handle.net/10220/12847 |
| work_keys_str_mv | AT lianghui handposeestimationbycombiningfingertiptrackingandarticulatedicp AT yuanjunsong handposeestimationbycombiningfingertiptrackingandarticulatedicp AT thalmanndaniel handposeestimationbycombiningfingertiptrackingandarticulatedicp |