[Recruitment]
Associate/Assistant Professor in Artificial Intelligence for Space-Enabled Technologies, Durham University

We are looking for applicants in Artificial Intelligence, Computer Vision, Edge Computing, Digital Twins, Human Computer Interaction, User Modelling, Robotics or Resilient Computing with potentials/achievements in informing space applications.

The post hoder will enjoy 1) a permanent (equivalent to US tenured) position at a top 100 university, 2) significantly reduced teaching, 3) a fully-funded PhD, 4) travel budget, 5) chance for a 2-year fully-funded Post-Doc.

Finding Repetitive Patterns in 3D Human Motion Captured Data

Jeff K. T. Tang, Howard Leung, Taku Komura and Hubert P. H. Shum
Proceedings of the 2008 International Conference on Ubiquitous Information Management and Communication (ICUIMC), 2008

 Citation: 24#

Finding Repetitive Patterns in 3D Human Motion Captured Data
# According to Google Scholar 2023"

Abstract

Finding repetitive patterns is important to many applications such as bioinformatics, finance and speech processing, etc. Repetitive patterns can be either cyclic or acyclic such that the patterns are continuous and distributed respectively. In this paper, we are going to find repetitive patterns in a given motion signal without prior knowledge about the type of motion. It is relatively easier to find repetitive patterns in discrete signal that contains a limited number of states by dynamic programming. However, it is impractical to identify exactly matched states in a continuous signal such as captured human motion data. A point cloud similarity of the input motion signal itself is considered and the longest similar patterns are located by tracing and extending matched posture pairs. Through pattern alignment and auto-clustering, cyclic and acyclic patterns are identified. Experiment results show that our approach can locate repetitive movements with small error rates.

Downloads

YouTube

Citations

BibTeX

@inproceedings{tang08finding,
 author={Tang, Jeff K. T. and Leung, Howard and Komura, Taku and Shum, Hubert P. H.},
 booktitle={Proceedings of the 2008 International Conference on Ubiquitous Information Management and Communication},
 series={ICUIMC '08},
 title={Finding Repetitive Patterns in 3D Human Motion Captured Data},
 year={2008},
 month={1},
 pages={396--403},
 numpages={8},
 doi={10.1145/1352793.1352876},
 isbn={978-1-59593-993-7},
 publisher={ACM},
 Address={New York, NY, USA},
 location={Suwon, Korea},
}

RIS

TY  - CONF
AU  - Tang, Jeff K. T.
AU  - Leung, Howard
AU  - Komura, Taku
AU  - Shum, Hubert P. H.
T2  - Proceedings of the 2008 International Conference on Ubiquitous Information Management and Communication
TI  - Finding Repetitive Patterns in 3D Human Motion Captured Data
PY  - 2008
Y1  - 1 2008
SP  - 396
EP  - 403
DO  - 10.1145/1352793.1352876
SN  - 978-1-59593-993-7
PB  - ACM
ER  - 

Plain Text

Jeff K. T. Tang, Howard Leung, Taku Komura and Hubert P. H. Shum, "Finding Repetitive Patterns in 3D Human Motion Captured Data," in ICUIMC '08: Proceedings of the 2008 International Conference on Ubiquitous Information Management and Communication, pp. 396-403, Suwon, Korea, ACM, Jan 2008.

Supporting Grants

Similar Research

Jeff K. T. Tang, Howard Leung, Taku Komura and Hubert P. H. Shum, "Emulating Human Perception of Motion Similarity", Computer Animation and Virtual Worlds (CAVW) - Proceedings of the 2008 International Conference on Computer Animation and Social Agents (CASA), 2008
Yang Yang, Huiwen Bian, Hubert P. H. Shum, Nauman Aslam and Lanling Zeng, "Temporal Clustering of Motion Capture Data with Optimal Partitioning", Proceedings of the 2016 International Conference on Virtual-Reality Continuum and its Applications in Industry (VRCAI), 2016
Shanfeng Hu, Worasak Rueangsirarak, Maxime Bouchee, Nauman Aslam and Hubert P. H. Shum, "A Motion Classification Approach to Fall Detection", Proceedings of the 2017 International Conference on Software, Knowledge, Information Management and Applications (SKIMA), 2017

 

 

Last updated on 24 February 2024
RSS Feed