Parsing 3D motion trajectory for gesture recognition
Motion trajectories have been widely used for gesture recognition. An effective representation of 3D motion trajectory is important for capturing and recognizing complex motion patterns. In this paper, we propose a view invariant hierarchical parsing method for free form 3D motion trajectory represe...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2017
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| Online Access: | https://hdl.handle.net/10356/86002 http://hdl.handle.net/10220/43907 |
| _version_ | 1811696763070840832 |
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| author | Yang, Jianyu Yuan, Junsong Li, Youfu |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Yang, Jianyu Yuan, Junsong Li, Youfu |
| author_sort | Yang, Jianyu |
| collection | NTU |
| description | Motion trajectories have been widely used for gesture recognition. An effective representation of 3D motion trajectory is important for capturing and recognizing complex motion patterns. In this paper, we propose a view invariant hierarchical parsing method for free form 3D motion trajectory representation. The raw motion trajectory is first parsed into four types of trajectory primitives based on their 3D shapes. These primitives are further segmented into sub-primitives by the proposed shape descriptors. Based on the clustered sub-primitives, trajectory recognition is achieved by using Hidden Markov Model. The proposed parsing approach is view-invariant in 3D space and is robust to variations of scale, temporary speed and partial occlusion. It well represents long motion trajectories can also support online gesture recognition. The proposed approach is evaluated on multiple benchmark datasets. The competitive experimental results and comparisons with the state-of-the-art methods verify the effectiveness of our approach. |
| first_indexed | 2024-10-01T07:44:32Z |
| format | Journal Article |
| id | ntu-10356/86002 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:44:32Z |
| publishDate | 2017 |
| record_format | dspace |
| spelling | ntu-10356/860022020-03-07T13:57:29Z Parsing 3D motion trajectory for gesture recognition Yang, Jianyu Yuan, Junsong Li, Youfu School of Electrical and Electronic Engineering 3D Trajectory Representation Motion Recognition Motion trajectories have been widely used for gesture recognition. An effective representation of 3D motion trajectory is important for capturing and recognizing complex motion patterns. In this paper, we propose a view invariant hierarchical parsing method for free form 3D motion trajectory representation. The raw motion trajectory is first parsed into four types of trajectory primitives based on their 3D shapes. These primitives are further segmented into sub-primitives by the proposed shape descriptors. Based on the clustered sub-primitives, trajectory recognition is achieved by using Hidden Markov Model. The proposed parsing approach is view-invariant in 3D space and is robust to variations of scale, temporary speed and partial occlusion. It well represents long motion trajectories can also support online gesture recognition. The proposed approach is evaluated on multiple benchmark datasets. The competitive experimental results and comparisons with the state-of-the-art methods verify the effectiveness of our approach. MOE (Min. of Education, S’pore) 2017-10-17T05:28:11Z 2019-12-06T16:14:08Z 2017-10-17T05:28:11Z 2019-12-06T16:14:08Z 2016 Journal Article Yang, J., Yuan, J., & Li, Y. (2016). Parsing 3D motion trajectory for gesture recognition. Journal of Visual Communication and Image Representation, 38, 627-640. 1047-3203 https://hdl.handle.net/10356/86002 http://hdl.handle.net/10220/43907 10.1016/j.jvcir.2016.04.010 en Journal of Visual Communication and Image Representation © 2016 Elsevier Inc. |
| spellingShingle | 3D Trajectory Representation Motion Recognition Yang, Jianyu Yuan, Junsong Li, Youfu Parsing 3D motion trajectory for gesture recognition |
| title | Parsing 3D motion trajectory for gesture recognition |
| title_full | Parsing 3D motion trajectory for gesture recognition |
| title_fullStr | Parsing 3D motion trajectory for gesture recognition |
| title_full_unstemmed | Parsing 3D motion trajectory for gesture recognition |
| title_short | Parsing 3D motion trajectory for gesture recognition |
| title_sort | parsing 3d motion trajectory for gesture recognition |
| topic | 3D Trajectory Representation Motion Recognition |
| url | https://hdl.handle.net/10356/86002 http://hdl.handle.net/10220/43907 |
| work_keys_str_mv | AT yangjianyu parsing3dmotiontrajectoryforgesturerecognition AT yuanjunsong parsing3dmotiontrajectoryforgesturerecognition AT liyoufu parsing3dmotiontrajectoryforgesturerecognition |