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.

Emulating Human Perception of Motion Similarity

Jeff K. T. Tang, Howard Leung, Taku Komura and Hubert P. H. Shum
Computer Animation and Virtual Worlds (CAVW) - Proceedings of the 2008 International Conference on Computer Animation and Social Agents (CASA), 2008

 Best Paper Award Impact Factor: 1.1 Citation: 77#

Emulating Human Perception of Motion Similarity
# According to Google Scholar 2023"


Evaluating the similarity of motions is useful for motion retrieval, motion blending, and performance analysis of dancers and athletes. Euclidean distance between corresponding joints has been widely adopted in measuring similarity of postures and hence motions. However, such a measure does not necessarily conform to the human perception of motion similarity. In this paper, we propose a new similarity measure based on machine learning techniques. We make use of the results of questionnaires from subjects answering whether arbitrary pairs of motions appear similar or not. Using the relative distance between the joints as the basic features, we train the system to compute the similarity of arbitrary pair of motions. Experimental results show that our method outperforms methods based on Euclidean distance between corresponding joints. Our method is applicable to content-based motion retrieval of human motion for large-scale database systems. It is also applicable to e-Learning systems which automatically evaluate the performance of dancers and athletes by comparing the subjects' motions with those by experts.





 author={Tang, Jeff K. T. and Leung, Howard and Komura, Taku and Shum, Hubert P. H.},
 journal={Computer Animation and Virtual Worlds},
 title={Emulating Human Perception of Motion Similarity},
 publisher={John Wiley and Sons Ltd.},
 Address={Chichester, UK},


AU  - Tang, Jeff K. T.
AU  - Leung, Howard
AU  - Komura, Taku
AU  - Shum, Hubert P. H.
T2  - Computer Animation and Virtual Worlds
TI  - Emulating Human Perception of Motion Similarity
PY  - 2008
VL  - 19
IS  - 3--4
SP  - 211
EP  - 221
DO  - 10.1002/cav.v19:3/4
SN  - 1546-4261
PB  - John Wiley and Sons Ltd.
ER  - 

Plain Text

Jeff K. T. Tang, Howard Leung, Taku Komura and Hubert P. H. Shum, "Emulating Human Perception of Motion Similarity," Computer Animation and Virtual Worlds, vol. 19, no. 3--4, pp. 211-221, John Wiley and Sons Ltd., 2008.

Supporting Grants

Similar Research

Jeff K. T. Tang, Howard Leung, Taku Komura and Hubert P. H. Shum, "Finding Repetitive Patterns in 3D Human Motion Captured Data", Proceedings of the 2008 International Conference on Ubiquitous Information Management and Communication (ICUIMC), 2008
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
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
Yijun Shen, Longzhi Yang, Edmond S. L. Ho and Hubert P. H. Shum, "Interaction-Based Human Activity Comparison", IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020
Ying Huang, Hubert P. H. Shum, Edmond S. L. Ho and Nauman Aslam, "High-Speed Multi-Person Pose Estimation with Deep Feature Transfer", Computer Vision and Image Understanding (CVIU), 2020



Last updated on 17 February 2024
RSS Feed