Dr Edmond S. L Ho

  • Senior Lecturer in Machine Learning (School of Computing Science)

Biography

Edmond Shu-lim Ho is currently a Senior Lecturer in the School of Computing Science (IDA-Section) at the University of Glasgow, Scotland, UK. Prior to joining the University of Glasgow in 2022, he was an Associate Professor in the Department of Computer and Information Sciences at Northumbria University, Newcastle upon Tyne, UK (2016-2022) and a Research Assistant Professor in the Department of Computer Science at Hong Kong Baptist University (2011-2016). He has been an Associate Editor of Computer Graphics Forum (CGF) since 2023. He received the BSc degree in Computer Science from the Hong Kong Baptist University, the MPhil degree from the City University of Hong Kong, and the PhD degree from the University of Edinburgh.

Research interests

My main research focuses on Machine Learning based approaches for solving problems in Computer Vision and Computer Graphics, with the main focus on analyzing and modelling human data captured from visual sensors. Such research topics provided solutions to a wide range of research problems, including human activity understanding, person re-identification, pose estimation and motion correction, character animation, motion retrieval, emotion analysis from body gestures and facial expressions.

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | 2005
Number of items: 72.

2024

Zhang, X., Meng, Z. , Lever, J. and Ho, E. S.L. (2024) Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), 23rd BioNLP Workshop, Bangkok, Thailand, 16 August 2024, (Accepted for Publication)

Zhu, M., Ho, E. S.L. , Chen, S., Yang, L. and Shum, H. P.H. (2024) Geometric features enhanced human-object interaction detection. IEEE Transactions on Instrumentation and Measurement, (Accepted for Publication)

Crosato, L., Wei, C., Ho, E. S. L. , Shum, H. P. H. and Sun, Y. (2024) A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection. In: 19th Annual ACM/IEEE International Conference on Human Robot Interaction (HRI 2024), Boulder, Colorado, USA, 11-15 March 2024, pp. 167-174. ISBN 9798400703225 (doi: 10.1145/3610977.3634923)

Zhang, H., Ho, E. S.L. , Zhang, X., Del Din, S. and Shum, H. P.H. (2024) Pose-based tremor type and level analysis for Parkinson’s disease from video. International Journal of Computer Assisted Radiology and Surgery, (doi: 10.1007/s11548-023-03052-4) (Early Online Publication)

Chazhoor, A. A. P., Ho, E. S.L. , Gao, B. and Woo, W. L. (2024) A review and benchmark on state-of-the-art steel defects detection. SN Computer Science, 5(1), 114. (doi: 10.1007/s42979-023-02436-2)

Crosato, L., Tian, K., Shum, H. P.H., Ho, E. S.L. , Wang, Y. and Wei, C. (2024) Social interaction-aware dynamical models and decision making for autonomous vehicles. Advanced Intelligent Systems, (doi: 10.1002/aisy.202300575) (Early Online Publication)

2023

Chen, S., Atapour-Abarghouei, A., Ho, E. S.L. and Shum, H. P.H. (2023) INCLG: inpainting for non-cleft lip generation with a multi-task image processing network. Software Impacts, 17, 100517. (doi: 10.1016/j.simpa.2023.100517)

Men, Q., Ho, E. S.L. , Shum, H. P.H. and Leung, H. (2023) Focalized contrastive view-invariant learning for self-supervised skeleton-based action recognition. Neurocomputing, 537, pp. 198-209. (doi: 10.1016/j.neucom.2023.03.070)

Sakkos, D., Ho, E. S.L. , Shum, H. P.H. and Elvin, G. (2023) Image editing-based data augmentation for illumination-insensitive background subtraction. Journal of Enterprise Information Management, 36(3), pp. 818-838. (doi: 10.1108/JEIM-02-2020-0042)

Crosato, L., Shum, H. P.H., Ho, E. S.L. and Wei, C. (2023) Interaction-aware decision-making for automated vehicles using social value orientation. IEEE Transactions on Intelligent Vehicles, 8(2), pp. 1339-1349. (doi: 10.1109/TIV.2022.3189836)

Hu, P., Ho, E. S.L. and Munteanu, A. (2023) Alignbodynet: deep learning-based alignment of non-overlapping partial body point clouds from a single depth camera. IEEE Transactions on Instrumentation and Measurement, 72, 2502609. (doi: 10.1109/TIM.2022.3222501)

2022

Goel, A., Men, Q. and Ho, E. S. L. (2022) Interaction mix and match: synthesizing close interaction using conditional hierarchical GAN with multi-hot class embedding. Computer Graphics Forum, 41(8), pp. 327-338. (doi: 10.1111/cgf.14647)

Hartley, J., Shum, H. P. H., Ho, E. S. L. , Wang, H. and Ramamoorthy, S. (2022) Formation control for UAVs using a Flux Guided approach. Expert Systems with Applications, 205, 117665. (doi: 10.1016/j.eswa.2022.117665)

Ho, E. S. L. , McCay, K. D., Marcroft, C. and Embleton, N. D. (2022) PCPP: a MATLAB application for abnormal infant movement detection from video. Software Impacts, 14, 100412. (doi: 10.1016/j.simpa.2022.100412)

Zhang, H., Ho, E. S.L. and Shum, H. P.H. (2022) CP-AGCN: Pytorch-based attention informed graph convolutional network for identifying infants at risk of cerebral palsy. Software Impacts, 14, 100419. (doi: 10.1016/j.simpa.2022.100419)

Zhu, M., Men, Q., Ho, E. S.L., Leung, H. and Shum, H. P.H. (2022) A two-stream convolutional network for musculoskeletal and neurological disorders prediction. Journal of Medical Systems, 46(11), 76. (doi: 10.1007/s10916-022-01857-5) (PMID:36201114) (PMCID:PMC9537228)

Zhang, H., Ho, E. S.L. , Zhang, X. and Shum, H. P.H. (2022) Pose-Based Tremor Classification for Parkinson's Disease Diagnosis from Video. In: Medical Image Computing and Computer Assisted Intervention — MICCAI 2022, Singapore, 18-22 Sep 2022, pp. 489-499. ISBN 9783031164392 (doi: 10.1007/978-3-031-16440-8_47)

Nozawa, N., Shum, H. P. H., Feng, Q., Ho, E. S. L. and Morishima, S. (2022) 3D car shape reconstruction from a contour sketch using GAN and lazy learning. Visual Computer, 38(4), pp. 1317-1330. (doi: 10.1007/s00371-020-02024-y)

Hu, P., Ho, E. S.-L. and Munteanu, A. (2022) 3DBodyNet: fast reconstruction of 3D animatable human body shape from a single commodity depth camera. IEEE Transactions on Multimedia, 24, pp. 2139-2149. (doi: 10.1109/TMM.2021.3076340)

McCay, K. D., Hu, P., Shum, H. P. H., Lok Woo, W., Marcroft, C., Embleton, N. D., Munteanu, A. and Ho, E. S. L. (2022) A pose-based feature fusion and classification framework for the early prediction of cerebral palsy in infants. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, pp. 8-19. (doi: 10.1109/TNSRE.2021.3138185) (PMID:34941512)

Thakur, D., Biswas, S., Ho, E. S. L. and Chattopadhyay, S. (2022) ConvAE-LSTM: convolutional autoencoder long short-term memory network for smartphone-based human activity recognition. IEEE Access, 10, pp. 4137-4156. (doi: 10.1109/ACCESS.2022.3140373)

2021

Men, Q., Ho, E. S. L. , Shum, H. P. H. and Leung, H. (2021) A quadruple diffusion convolutional recurrent network for human motion prediction. IEEE Transactions on Circuits and Systems for Video Technology, 31(9), pp. 3417-3432. (doi: 10.1109/TCSVT.2020.3038145)

Chan, J. C. P. and Ho, E. S. L. (2021) Emotion transfer for 3D hand and full body motion using StarGAN. Computers, 10(3), 38. (doi: 10.3390/computers10030038)

Wang, H., Ho, E. S. L. , Shum, H. P. H. and Zhu, Z. (2021) Spatio-temporal manifold learning for human motions via long-horizon modeling. IEEE Transactions on Visualization and Computer Graphics, 27(1), pp. 216-227. (doi: 10.1109/TVCG.2019.2936810) (PMID:31443030)

Hammad, M., Iliyasu, A. M., Subasi, A., Ho, E. S. L. and Abd El-Latif, A. A. (2021) A multitier deep learning model for arrhythmia detection. IEEE Transactions on Instrumentation and Measurement, 70, 2502809. (doi: 10.1109/TIM.2020.3033072)

Kar, A., Pramanik, S., Chakraborty, A., Bhattacharjee, D., Ho, E. S. L. and Shum, H. P. H. (2021) LMZMPM: Local Modified Zernike Moment per-unit Mass for robust human face recognition. IEEE Transactions on Information Forensics and Security, 16, pp. 495-509. (doi: 10.1109/TIFS.2020.3015552)

Sakkos, D., Mccay, K. D., Marcroft, C., Embleton, N. D., Chattopadhyay, S. and Ho, E. S. L. (2021) Identification of abnormal movements in infants: a deep neural network for body part-based prediction of cerebral palsy. IEEE Access, 9, pp. 94281-94292. (doi: 10.1109/ACCESS.2021.3093469)

2020

Shen, Y., Yang, L., Ho, E. S.L. and Shum, H. P.H. (2020) Interaction-based human activity comparison. IEEE Transactions on Visualization and Computer Graphics, 26(8), pp. 2620-2633. (doi: 10.1109/TVCG.2019.2893247) (PMID:30703028)

Organisciak, D., Sakkos, D., Ho, E. S.L. , Aslam, N. and Shum, H. P. H. (2020) Unifying person and vehicle re-identification. IEEE Access, 8, pp. 115673-115684. (doi: 10.1109/ACCESS.2020.3004092)

McCay, K. D., Ho, E. S.L. , Shum, H. P.H., Fehringer, G., Marcroft, C. and Embleton, N. D. (2020) Abnormal infant movements classification with deep learning on pose-based features. IEEE Access, 8, pp. 51582-51592. (doi: 10.1109/ACCESS.2020.2980269)

2019

Stef, A., Perera, K., Shum, H.P.H. and Ho, E.S.L. (2019) Synthesizing Expressive Facial and Speech Animation by Text-to-IPA Translation with Emotion Control. In: 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), Phnom Penh, Cambodia, 03-05 December 2018, ISBN 9781538691410 (doi: 10.1109/SKIMA.2018.8631536)

Chan, J. C.P., Shum, H. P.H., Wang, H., Yi, L., Wei, W. and Ho, E. S.L. (2019) A generic framework for editing and synthesizing multimodal data with relative emotion strength. Computer Animation and Virtual Worlds, 30(6), e1871. (doi: 10.1002/cav.1871)

Hall, J., Chan, J.C.P., Shum, H.P.H., Wei, W. and Ho, E.S.L. (2019) An Interactive Motion Analysis Framework for Diagnosing and Rectifying Potential Injuries Caused Through Resistance Training. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364688)

Zhang, J., Shum, H.P.H., McCay, K. and Ho, E.S.L. (2019) Prior-Less 3D Human Shape Reconstruction with an Earth Mover’s Distance Informed CNN. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364694)

McCay, K.D., Ho, E.S.L. , Marcroft, C. and Embleton, N.D. (2019) Establishing Pose Based Features Using Histograms for the Detection of Abnormal Infant Movements. In: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 23-27 July 2019, pp. 5469-5472. (doi: 10.1109/EMBC.2019.8857680)

Hu, P., Ho, E.S.L. , Aslam, N., Shum, H.P.H. and Komura, T. (2019) A new method to evaluate the dynamic air gap thickness and garment sliding of virtual clothes during walking. Textile Research Journal, 89(19-20), pp. 4148-4161. (doi: 10.1177/0040517519826930)

Irimia, A.-S., Chan, J.C.P., Mistry, K., Wei, W. and Ho, E.S.L. (2019) Emotion Transfer for Hand Animation. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364692)

Nozawa, N., Shum, H.P.H., Ho, E.S.L. and Morishima, S. (2019) 3D car shape reconstruction from a single sketch image. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364693)

Sakkos, D., Ho, E. S. L. and Shum, H. P. H. (2019) Illumination-aware multi-task GANs for foreground segmentation. IEEE Access, 7, pp. 10976-10986. (doi: 10.1109/ACCESS.2019.2891943)

Xu, S., Ho, E.S.L. and Shum, H.P.H. (2019) A hybrid metaheuristic navigation algorithm for robot path rolling planning in an unknown environment. Mechatronic Systems and Control, 47(4), pp. 216-224. (doi: 10.2316/J.2019.201-3000)

2018

Flinton, C., Anderson, P., Shum, H.P.H. and Ho, E.S.L. (2018) NETIVAR: NETwork Information Visualization based on Augmented Reality. In: 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), Phnom Penh, Cambodia, 03-05 December 2018, ISBN 9781538691410 (doi: 10.1109/SKIMA.2018.8631530)

Rueangsirarak, W., Zhang, J., Aslam, N., Ho, E. S.L. and Shum, H. P.H. (2018) Automatic musculoskeletal and neurological disorder diagnosis with relative joint displacement from human gait. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(12), pp. 2387-2396. (doi: 10.1109/TNSRE.2018.2880871) (PMID:30442608)

Li, J., Qu, Y., Chao, F., Shum, H.P.H., Ho, E.S.L. and Yang, L. (2018) Machine learning algorithms for network intrusion detection. In: AI in Cybersecurity. Series: Intelligent systems reference library, 151. Springer, pp. 151-179. ISBN 9783319988412 (doi: 10.1007/978-3-319-98842-9_6)

Shen, Y., Henry, J., Wang, H., Ho, E. S.L. , Komura, T. and Shum, H. P. H. (2018) Data-driven crowd motion control with multi-touch gestures. Computer Graphics Forum, 37(6), pp. 382-394. (doi: 10.1111/cgf.13333)

Yin, K., Huang, H., Ho, E.S.L. , Wang, H., Komura, T., Cohen-Or, D. and Zhang, H. (2018) A sampling approach to generating closely interacting 3D pose-pairs from 2D annotations. IEEE Transactions on Visualization and Computer Graphics, 25(6), pp. 2217-2227. (doi: 10.1109/TVCG.2018.2832097) (PMID:29994049)

Ho, E. S.L. and Yuen, P. C. (2018) Real-time full-body pose synthesis and editing. In: Müller, B. and Wolf, S. I. (eds.) Handbook of Human Motion. Springer, pp. 1959-1974. ISBN 9783319144184 (doi: 10.1007/978-3-319-14418-4_8.)

Xu, S., Ho, E.S.L. , Aslam, N. and Shum, H.P.H. (2018) Unsupervised abnormal behaviour detection with overhead crowd video. In: 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Malabe, Sri Lanka, 6-8 December 2017, ISBN 9781538646021 (doi: 10.1109/SKIMA.2017.8294092)

2017

Shen, Y., Wang, H., Ho, E.S.L. , Yang, L. and Shum, H.P.H. (2017) Posture-based and action-based graphs for boxing skill visualization. Computers and Graphics, 69, pp. 104-115. (doi: 10.1016/j.cag.2017.09.007)

2016

Shum, H.P.H., Wang, H., Ho, E.S.L. and Komura, T. (2016) SkillVis: a visualization tool for boxing skill assessment. In: MiG '16: Motion In Games, 10 - 12 October 2016, Burlingame, CA, USA, pp. 145-153. ISBN 9781450345927 (doi: 10.1145/2994258.2994266)

Ho, E. S.L. , Chan, J. C.P., Chan, D. C.K., Shum, H. P.H., Cheung, Y.-m. and Yuen, P. C. (2016) Improving posture classification accuracy for depth sensor-based human activity monitoring in smart environments. Computer Vision and Image Understanding, 148, pp. 97-110. (doi: 10.1016/j.cviu.2015.12.011)

2015

Ho, E.S.L. , Chan, J.C.P., Cheung, Y.-M. and Yuen, P.C. (2015) Modeling Spatial Relations of Human Body Parts for Indexing and Retrieving Close Character Interactions. In: VRST '15: 21th ACM Symposium on Virtual Reality Software and Technology, Beijing China, 13 - 15 November 2015, pp. 187-190. ISBN 9781450339902 (doi: 10.1145/2821592.2821617)

Wong, C. K. and Ho, E. S. L. (2015) A Study of Performance Difference of Students Admitted Through Different Routes in a Systems Analysis and Design Course. 3rd Asia Symposium on Engineering and Information, Chengdu, China, 23-25 April 2015.

2014

Ho, E. S.L. , Wang, H. and Komura, T. (2014) A multi-resolution approach for adapting close character interaction. In: VRST '14: Proceedings of the 20th ACM Symposium on Virtual Reality Software and Technology, Edinburgh, Scotland, 11 - 13 November 2014, 97 - 106. ISBN 9781450332538 (doi: 10.1145/2671015.2671020)

Shum, H. P.H., Hoyet, L., Ho, E. S.L. , Komura, T. and Multon, F. (2014) Natural preparation behavior synthesis. Computer Animation and Virtual Worlds, 25, 531 - 542. (doi: 10.1002/cav.1546)

Wang, H., Ho, E. S.L. and Komura, T. (2014) An energy-driven motion planning method for two distant postures. IEEE Transactions on Visualization and Computer Graphics, 21(1), 18 - 30. (doi: 10.1109/TVCG.2014.2327976)

2013

Ho, E. S.L. , Shum, H. P.H., Cheung, Y.-m. and Yuen, P. C. (2013) Topology aware data-driven inverse kinematics. Computer Graphics Forum, 32(7), 61 - 70. (doi: 10.1111/cgf.12212)

Ho, E. S.L. and Shum, H. P.H. (2013) Motion Adaptation for Humanoid Robots in Constrained Environments. In: 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 6-10 May 2013, 3813 - 3818. ISBN 9781467356435 (doi: 10.1109/ICRA.2013.6631113)

Shum, H. P. H., Ho, E. S.L. , Jiang, Y. and Takagi, S. (2013) Real-time posture reconstruction for Microsoft Kinect. IEEE Transactions on Cybernetics, 43(5), 1357 - 1369. (doi: 10.1109/TCYB.2013.2275945)

Ho, E. S.L. , Chan, J. C.P., Komura, T. and Leung, H. (2013) Interactive partner control in close interactions for real-time applications. ACM Transactions on Multimedia Computing, Communications and Applications, 9(3), 21. (doi: 10.1145/2487268.2487274)

Shum, H. P.H., Hoyet, L., Ho, E. S.L. , Komura, T. and Multon, F. (2013) Preparation Behaviour Synthesis with Reinforcement Learning. CASA 2013 : The 26th Conference on Computer Animation and Social Agents, Istanbul, Turkey, 16-18 May 2013.

2012

Shum, H. P.H. and Ho, E. S.L. (2012) Real-Time Physical Modelling of Character Movements with Microsoft Kinect. In: VRST'12: The 18th ACM Symposium on Virtual Reality Software and Technology 2012, Toronto, Canada, 10 - 12 December 2012, pp. 17-24. ISBN 9781450314695 (doi: 10.1145/2407336)

2011

Ho, E. S.L. and Komura, T. (2011) A finite state machine based on topology coordinates for wrestling games. Computer Animation and Virtual Worlds, 22(5), 435 - 443. (doi: 10.1002/cav.376)

2010

Ho, E.S.L. , Komura, T., Ramamoorthy, S. and Vijayakumar, S. (2010) Controlling Humanoid Robots in Topology Coordinates. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18-22 October 2010, pp. 178-182. ISBN 9781424466764 (doi: 10.1109/IROS.2010.5652787)

Ho, E. S.L. , Komura, T. and Tai, C.-L. (2010) Spatial relationship preserving character motion adaptation. ACM Transactions on Graphics, 29(4), 33. (doi: 10.1145/1778765.1778770)

2009

Ho, E. S.L. and Komura, T. (2009) Real-time character control for wrestling games. In: Egges, A., Geraerts, R. and Overmars, M. (eds.) Motion in Games. Series: Lecture notes in computer science (5884). Springer, pp. 128-137. ISBN 9783642103469 (doi: 10.1007/978-3-642-10347-6_12)

Ho, E.S.L. and Komura, T. (2009) Planning Tangling Motions for Humanoids. In: 2007 7th IEEE-RAS International Conference on Humanoid Robots, Pittsburgh, PA, USA, 29 November - 1 December 2007, pp. 507-512. ISBN 9781424418619 (doi: 10.1109/ICHR.2007.4813918)

Ho, E. S.L. and Komura, T. (2009) Character motion synthesis by topology coordinates. Computer Graphics Forum, 28(2), pp. 299-308. (doi: 10.1111/j.1467-8659.2009.01369.x)

Ho, E.S.L. and Komura, T. (2009) Indexing and retrieving motions of characters in close contact. IEEE Transactions on Visualization and Computer Graphics, 15(3), pp. 481-492. (doi: 10.1109/TVCG.2008.199) (PMID:19282553)

2008

Komura, T., Shum, H.P.H. and Ho, E.S.L. (2008) Simulating interactions of characters. In: Egges, A., Kamphuis, A. and Overmars, M. (eds.) Motion in Games. Series: Lecture notes in computer science (5277). Springer, pp. 94-103. ISBN 9783540892199 (doi: 10.1007/978-3-540-89220-5-10)

2007

Ho, E. S.L. and Komura, T. (2007) Wrestle Alone : Creating Tangled Motions of Multiple Avatars from Individually Captured Motions. In: 15th Pacific Conference on Computer Graphics and Applications (PG'07), Maui, HI, USA, 29 October- 2 November 2007, ISBN 9780769530093 (doi: 10.1109/pg.2007.54)

2005

Ho, E.S.L. , Komura, T. and Lau, R.W.H. (2005) Computing Inverse Kinematics with Linear Programming. In: VRST05: The ACM Symposium on Virtual Reality Software and Technology 2005, Monterey, CA, USA, 7 - 9 November 2005, pp. 163-166. ISBN 1595930981 (doi: 10.1145/1101616.1101651)

Komura, T., Ho, E.S.L. and Lau, R.W.H. (2005) Animating reactive motion using momentum-based inverse kinematics. Computer Animation and Virtual Worlds, 16(3-4), pp. 213-223. (doi: 10.1002/cav.101)

This list was generated on Fri Jul 12 07:07:41 2024 BST.
Number of items: 72.

Articles

Zhu, M., Ho, E. S.L. , Chen, S., Yang, L. and Shum, H. P.H. (2024) Geometric features enhanced human-object interaction detection. IEEE Transactions on Instrumentation and Measurement, (Accepted for Publication)

Zhang, H., Ho, E. S.L. , Zhang, X., Del Din, S. and Shum, H. P.H. (2024) Pose-based tremor type and level analysis for Parkinson’s disease from video. International Journal of Computer Assisted Radiology and Surgery, (doi: 10.1007/s11548-023-03052-4) (Early Online Publication)

Chazhoor, A. A. P., Ho, E. S.L. , Gao, B. and Woo, W. L. (2024) A review and benchmark on state-of-the-art steel defects detection. SN Computer Science, 5(1), 114. (doi: 10.1007/s42979-023-02436-2)

Crosato, L., Tian, K., Shum, H. P.H., Ho, E. S.L. , Wang, Y. and Wei, C. (2024) Social interaction-aware dynamical models and decision making for autonomous vehicles. Advanced Intelligent Systems, (doi: 10.1002/aisy.202300575) (Early Online Publication)

Chen, S., Atapour-Abarghouei, A., Ho, E. S.L. and Shum, H. P.H. (2023) INCLG: inpainting for non-cleft lip generation with a multi-task image processing network. Software Impacts, 17, 100517. (doi: 10.1016/j.simpa.2023.100517)

Men, Q., Ho, E. S.L. , Shum, H. P.H. and Leung, H. (2023) Focalized contrastive view-invariant learning for self-supervised skeleton-based action recognition. Neurocomputing, 537, pp. 198-209. (doi: 10.1016/j.neucom.2023.03.070)

Sakkos, D., Ho, E. S.L. , Shum, H. P.H. and Elvin, G. (2023) Image editing-based data augmentation for illumination-insensitive background subtraction. Journal of Enterprise Information Management, 36(3), pp. 818-838. (doi: 10.1108/JEIM-02-2020-0042)

Crosato, L., Shum, H. P.H., Ho, E. S.L. and Wei, C. (2023) Interaction-aware decision-making for automated vehicles using social value orientation. IEEE Transactions on Intelligent Vehicles, 8(2), pp. 1339-1349. (doi: 10.1109/TIV.2022.3189836)

Hu, P., Ho, E. S.L. and Munteanu, A. (2023) Alignbodynet: deep learning-based alignment of non-overlapping partial body point clouds from a single depth camera. IEEE Transactions on Instrumentation and Measurement, 72, 2502609. (doi: 10.1109/TIM.2022.3222501)

Goel, A., Men, Q. and Ho, E. S. L. (2022) Interaction mix and match: synthesizing close interaction using conditional hierarchical GAN with multi-hot class embedding. Computer Graphics Forum, 41(8), pp. 327-338. (doi: 10.1111/cgf.14647)

Hartley, J., Shum, H. P. H., Ho, E. S. L. , Wang, H. and Ramamoorthy, S. (2022) Formation control for UAVs using a Flux Guided approach. Expert Systems with Applications, 205, 117665. (doi: 10.1016/j.eswa.2022.117665)

Ho, E. S. L. , McCay, K. D., Marcroft, C. and Embleton, N. D. (2022) PCPP: a MATLAB application for abnormal infant movement detection from video. Software Impacts, 14, 100412. (doi: 10.1016/j.simpa.2022.100412)

Zhang, H., Ho, E. S.L. and Shum, H. P.H. (2022) CP-AGCN: Pytorch-based attention informed graph convolutional network for identifying infants at risk of cerebral palsy. Software Impacts, 14, 100419. (doi: 10.1016/j.simpa.2022.100419)

Zhu, M., Men, Q., Ho, E. S.L., Leung, H. and Shum, H. P.H. (2022) A two-stream convolutional network for musculoskeletal and neurological disorders prediction. Journal of Medical Systems, 46(11), 76. (doi: 10.1007/s10916-022-01857-5) (PMID:36201114) (PMCID:PMC9537228)

Nozawa, N., Shum, H. P. H., Feng, Q., Ho, E. S. L. and Morishima, S. (2022) 3D car shape reconstruction from a contour sketch using GAN and lazy learning. Visual Computer, 38(4), pp. 1317-1330. (doi: 10.1007/s00371-020-02024-y)

Hu, P., Ho, E. S.-L. and Munteanu, A. (2022) 3DBodyNet: fast reconstruction of 3D animatable human body shape from a single commodity depth camera. IEEE Transactions on Multimedia, 24, pp. 2139-2149. (doi: 10.1109/TMM.2021.3076340)

McCay, K. D., Hu, P., Shum, H. P. H., Lok Woo, W., Marcroft, C., Embleton, N. D., Munteanu, A. and Ho, E. S. L. (2022) A pose-based feature fusion and classification framework for the early prediction of cerebral palsy in infants. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 30, pp. 8-19. (doi: 10.1109/TNSRE.2021.3138185) (PMID:34941512)

Thakur, D., Biswas, S., Ho, E. S. L. and Chattopadhyay, S. (2022) ConvAE-LSTM: convolutional autoencoder long short-term memory network for smartphone-based human activity recognition. IEEE Access, 10, pp. 4137-4156. (doi: 10.1109/ACCESS.2022.3140373)

Men, Q., Ho, E. S. L. , Shum, H. P. H. and Leung, H. (2021) A quadruple diffusion convolutional recurrent network for human motion prediction. IEEE Transactions on Circuits and Systems for Video Technology, 31(9), pp. 3417-3432. (doi: 10.1109/TCSVT.2020.3038145)

Chan, J. C. P. and Ho, E. S. L. (2021) Emotion transfer for 3D hand and full body motion using StarGAN. Computers, 10(3), 38. (doi: 10.3390/computers10030038)

Wang, H., Ho, E. S. L. , Shum, H. P. H. and Zhu, Z. (2021) Spatio-temporal manifold learning for human motions via long-horizon modeling. IEEE Transactions on Visualization and Computer Graphics, 27(1), pp. 216-227. (doi: 10.1109/TVCG.2019.2936810) (PMID:31443030)

Hammad, M., Iliyasu, A. M., Subasi, A., Ho, E. S. L. and Abd El-Latif, A. A. (2021) A multitier deep learning model for arrhythmia detection. IEEE Transactions on Instrumentation and Measurement, 70, 2502809. (doi: 10.1109/TIM.2020.3033072)

Kar, A., Pramanik, S., Chakraborty, A., Bhattacharjee, D., Ho, E. S. L. and Shum, H. P. H. (2021) LMZMPM: Local Modified Zernike Moment per-unit Mass for robust human face recognition. IEEE Transactions on Information Forensics and Security, 16, pp. 495-509. (doi: 10.1109/TIFS.2020.3015552)

Sakkos, D., Mccay, K. D., Marcroft, C., Embleton, N. D., Chattopadhyay, S. and Ho, E. S. L. (2021) Identification of abnormal movements in infants: a deep neural network for body part-based prediction of cerebral palsy. IEEE Access, 9, pp. 94281-94292. (doi: 10.1109/ACCESS.2021.3093469)

Shen, Y., Yang, L., Ho, E. S.L. and Shum, H. P.H. (2020) Interaction-based human activity comparison. IEEE Transactions on Visualization and Computer Graphics, 26(8), pp. 2620-2633. (doi: 10.1109/TVCG.2019.2893247) (PMID:30703028)

Organisciak, D., Sakkos, D., Ho, E. S.L. , Aslam, N. and Shum, H. P. H. (2020) Unifying person and vehicle re-identification. IEEE Access, 8, pp. 115673-115684. (doi: 10.1109/ACCESS.2020.3004092)

McCay, K. D., Ho, E. S.L. , Shum, H. P.H., Fehringer, G., Marcroft, C. and Embleton, N. D. (2020) Abnormal infant movements classification with deep learning on pose-based features. IEEE Access, 8, pp. 51582-51592. (doi: 10.1109/ACCESS.2020.2980269)

Chan, J. C.P., Shum, H. P.H., Wang, H., Yi, L., Wei, W. and Ho, E. S.L. (2019) A generic framework for editing and synthesizing multimodal data with relative emotion strength. Computer Animation and Virtual Worlds, 30(6), e1871. (doi: 10.1002/cav.1871)

Hu, P., Ho, E.S.L. , Aslam, N., Shum, H.P.H. and Komura, T. (2019) A new method to evaluate the dynamic air gap thickness and garment sliding of virtual clothes during walking. Textile Research Journal, 89(19-20), pp. 4148-4161. (doi: 10.1177/0040517519826930)

Sakkos, D., Ho, E. S. L. and Shum, H. P. H. (2019) Illumination-aware multi-task GANs for foreground segmentation. IEEE Access, 7, pp. 10976-10986. (doi: 10.1109/ACCESS.2019.2891943)

Xu, S., Ho, E.S.L. and Shum, H.P.H. (2019) A hybrid metaheuristic navigation algorithm for robot path rolling planning in an unknown environment. Mechatronic Systems and Control, 47(4), pp. 216-224. (doi: 10.2316/J.2019.201-3000)

Rueangsirarak, W., Zhang, J., Aslam, N., Ho, E. S.L. and Shum, H. P.H. (2018) Automatic musculoskeletal and neurological disorder diagnosis with relative joint displacement from human gait. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 26(12), pp. 2387-2396. (doi: 10.1109/TNSRE.2018.2880871) (PMID:30442608)

Shen, Y., Henry, J., Wang, H., Ho, E. S.L. , Komura, T. and Shum, H. P. H. (2018) Data-driven crowd motion control with multi-touch gestures. Computer Graphics Forum, 37(6), pp. 382-394. (doi: 10.1111/cgf.13333)

Yin, K., Huang, H., Ho, E.S.L. , Wang, H., Komura, T., Cohen-Or, D. and Zhang, H. (2018) A sampling approach to generating closely interacting 3D pose-pairs from 2D annotations. IEEE Transactions on Visualization and Computer Graphics, 25(6), pp. 2217-2227. (doi: 10.1109/TVCG.2018.2832097) (PMID:29994049)

Shen, Y., Wang, H., Ho, E.S.L. , Yang, L. and Shum, H.P.H. (2017) Posture-based and action-based graphs for boxing skill visualization. Computers and Graphics, 69, pp. 104-115. (doi: 10.1016/j.cag.2017.09.007)

Ho, E. S.L. , Chan, J. C.P., Chan, D. C.K., Shum, H. P.H., Cheung, Y.-m. and Yuen, P. C. (2016) Improving posture classification accuracy for depth sensor-based human activity monitoring in smart environments. Computer Vision and Image Understanding, 148, pp. 97-110. (doi: 10.1016/j.cviu.2015.12.011)

Shum, H. P.H., Hoyet, L., Ho, E. S.L. , Komura, T. and Multon, F. (2014) Natural preparation behavior synthesis. Computer Animation and Virtual Worlds, 25, 531 - 542. (doi: 10.1002/cav.1546)

Wang, H., Ho, E. S.L. and Komura, T. (2014) An energy-driven motion planning method for two distant postures. IEEE Transactions on Visualization and Computer Graphics, 21(1), 18 - 30. (doi: 10.1109/TVCG.2014.2327976)

Ho, E. S.L. , Shum, H. P.H., Cheung, Y.-m. and Yuen, P. C. (2013) Topology aware data-driven inverse kinematics. Computer Graphics Forum, 32(7), 61 - 70. (doi: 10.1111/cgf.12212)

Shum, H. P. H., Ho, E. S.L. , Jiang, Y. and Takagi, S. (2013) Real-time posture reconstruction for Microsoft Kinect. IEEE Transactions on Cybernetics, 43(5), 1357 - 1369. (doi: 10.1109/TCYB.2013.2275945)

Ho, E. S.L. , Chan, J. C.P., Komura, T. and Leung, H. (2013) Interactive partner control in close interactions for real-time applications. ACM Transactions on Multimedia Computing, Communications and Applications, 9(3), 21. (doi: 10.1145/2487268.2487274)

Ho, E. S.L. and Komura, T. (2011) A finite state machine based on topology coordinates for wrestling games. Computer Animation and Virtual Worlds, 22(5), 435 - 443. (doi: 10.1002/cav.376)

Ho, E. S.L. , Komura, T. and Tai, C.-L. (2010) Spatial relationship preserving character motion adaptation. ACM Transactions on Graphics, 29(4), 33. (doi: 10.1145/1778765.1778770)

Ho, E. S.L. and Komura, T. (2009) Character motion synthesis by topology coordinates. Computer Graphics Forum, 28(2), pp. 299-308. (doi: 10.1111/j.1467-8659.2009.01369.x)

Ho, E.S.L. and Komura, T. (2009) Indexing and retrieving motions of characters in close contact. IEEE Transactions on Visualization and Computer Graphics, 15(3), pp. 481-492. (doi: 10.1109/TVCG.2008.199) (PMID:19282553)

Komura, T., Ho, E.S.L. and Lau, R.W.H. (2005) Animating reactive motion using momentum-based inverse kinematics. Computer Animation and Virtual Worlds, 16(3-4), pp. 213-223. (doi: 10.1002/cav.101)

Book Sections

Li, J., Qu, Y., Chao, F., Shum, H.P.H., Ho, E.S.L. and Yang, L. (2018) Machine learning algorithms for network intrusion detection. In: AI in Cybersecurity. Series: Intelligent systems reference library, 151. Springer, pp. 151-179. ISBN 9783319988412 (doi: 10.1007/978-3-319-98842-9_6)

Ho, E. S.L. and Yuen, P. C. (2018) Real-time full-body pose synthesis and editing. In: Müller, B. and Wolf, S. I. (eds.) Handbook of Human Motion. Springer, pp. 1959-1974. ISBN 9783319144184 (doi: 10.1007/978-3-319-14418-4_8.)

Ho, E. S.L. and Komura, T. (2009) Real-time character control for wrestling games. In: Egges, A., Geraerts, R. and Overmars, M. (eds.) Motion in Games. Series: Lecture notes in computer science (5884). Springer, pp. 128-137. ISBN 9783642103469 (doi: 10.1007/978-3-642-10347-6_12)

Komura, T., Shum, H.P.H. and Ho, E.S.L. (2008) Simulating interactions of characters. In: Egges, A., Kamphuis, A. and Overmars, M. (eds.) Motion in Games. Series: Lecture notes in computer science (5277). Springer, pp. 94-103. ISBN 9783540892199 (doi: 10.1007/978-3-540-89220-5-10)

Conference or Workshop Item

Wong, C. K. and Ho, E. S. L. (2015) A Study of Performance Difference of Students Admitted Through Different Routes in a Systems Analysis and Design Course. 3rd Asia Symposium on Engineering and Information, Chengdu, China, 23-25 April 2015.

Shum, H. P.H., Hoyet, L., Ho, E. S.L. , Komura, T. and Multon, F. (2013) Preparation Behaviour Synthesis with Reinforcement Learning. CASA 2013 : The 26th Conference on Computer Animation and Social Agents, Istanbul, Turkey, 16-18 May 2013.

Conference Proceedings

Zhang, X., Meng, Z. , Lever, J. and Ho, E. S.L. (2024) Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), 23rd BioNLP Workshop, Bangkok, Thailand, 16 August 2024, (Accepted for Publication)

Crosato, L., Wei, C., Ho, E. S. L. , Shum, H. P. H. and Sun, Y. (2024) A Virtual Reality Framework for Human-Driver Interaction Research: Safe and Cost-Effective Data Collection. In: 19th Annual ACM/IEEE International Conference on Human Robot Interaction (HRI 2024), Boulder, Colorado, USA, 11-15 March 2024, pp. 167-174. ISBN 9798400703225 (doi: 10.1145/3610977.3634923)

Zhang, H., Ho, E. S.L. , Zhang, X. and Shum, H. P.H. (2022) Pose-Based Tremor Classification for Parkinson's Disease Diagnosis from Video. In: Medical Image Computing and Computer Assisted Intervention — MICCAI 2022, Singapore, 18-22 Sep 2022, pp. 489-499. ISBN 9783031164392 (doi: 10.1007/978-3-031-16440-8_47)

Stef, A., Perera, K., Shum, H.P.H. and Ho, E.S.L. (2019) Synthesizing Expressive Facial and Speech Animation by Text-to-IPA Translation with Emotion Control. In: 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), Phnom Penh, Cambodia, 03-05 December 2018, ISBN 9781538691410 (doi: 10.1109/SKIMA.2018.8631536)

Hall, J., Chan, J.C.P., Shum, H.P.H., Wei, W. and Ho, E.S.L. (2019) An Interactive Motion Analysis Framework for Diagnosing and Rectifying Potential Injuries Caused Through Resistance Training. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364688)

Zhang, J., Shum, H.P.H., McCay, K. and Ho, E.S.L. (2019) Prior-Less 3D Human Shape Reconstruction with an Earth Mover’s Distance Informed CNN. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364694)

McCay, K.D., Ho, E.S.L. , Marcroft, C. and Embleton, N.D. (2019) Establishing Pose Based Features Using Histograms for the Detection of Abnormal Infant Movements. In: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 23-27 July 2019, pp. 5469-5472. (doi: 10.1109/EMBC.2019.8857680)

Irimia, A.-S., Chan, J.C.P., Mistry, K., Wei, W. and Ho, E.S.L. (2019) Emotion Transfer for Hand Animation. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364692)

Nozawa, N., Shum, H.P.H., Ho, E.S.L. and Morishima, S. (2019) 3D car shape reconstruction from a single sketch image. In: MIG '19: Motion, Interaction and Games, Newcastle upon Tyne, UK, 28 - 30 October 2019, pp. 1-2. ISBN 9781450369947 (doi: 10.1145/3359566.3364693)

Flinton, C., Anderson, P., Shum, H.P.H. and Ho, E.S.L. (2018) NETIVAR: NETwork Information Visualization based on Augmented Reality. In: 2018 12th International Conference on Software, Knowledge, Information Management & Applications (SKIMA), Phnom Penh, Cambodia, 03-05 December 2018, ISBN 9781538691410 (doi: 10.1109/SKIMA.2018.8631530)

Xu, S., Ho, E.S.L. , Aslam, N. and Shum, H.P.H. (2018) Unsupervised abnormal behaviour detection with overhead crowd video. In: 2017 11th International Conference on Software, Knowledge, Information Management and Applications (SKIMA), Malabe, Sri Lanka, 6-8 December 2017, ISBN 9781538646021 (doi: 10.1109/SKIMA.2017.8294092)

Shum, H.P.H., Wang, H., Ho, E.S.L. and Komura, T. (2016) SkillVis: a visualization tool for boxing skill assessment. In: MiG '16: Motion In Games, 10 - 12 October 2016, Burlingame, CA, USA, pp. 145-153. ISBN 9781450345927 (doi: 10.1145/2994258.2994266)

Ho, E.S.L. , Chan, J.C.P., Cheung, Y.-M. and Yuen, P.C. (2015) Modeling Spatial Relations of Human Body Parts for Indexing and Retrieving Close Character Interactions. In: VRST '15: 21th ACM Symposium on Virtual Reality Software and Technology, Beijing China, 13 - 15 November 2015, pp. 187-190. ISBN 9781450339902 (doi: 10.1145/2821592.2821617)

Ho, E. S.L. , Wang, H. and Komura, T. (2014) A multi-resolution approach for adapting close character interaction. In: VRST '14: Proceedings of the 20th ACM Symposium on Virtual Reality Software and Technology, Edinburgh, Scotland, 11 - 13 November 2014, 97 - 106. ISBN 9781450332538 (doi: 10.1145/2671015.2671020)

Ho, E. S.L. and Shum, H. P.H. (2013) Motion Adaptation for Humanoid Robots in Constrained Environments. In: 2013 IEEE International Conference on Robotics and Automation (ICRA), Karlsruhe, Germany, 6-10 May 2013, 3813 - 3818. ISBN 9781467356435 (doi: 10.1109/ICRA.2013.6631113)

Shum, H. P.H. and Ho, E. S.L. (2012) Real-Time Physical Modelling of Character Movements with Microsoft Kinect. In: VRST'12: The 18th ACM Symposium on Virtual Reality Software and Technology 2012, Toronto, Canada, 10 - 12 December 2012, pp. 17-24. ISBN 9781450314695 (doi: 10.1145/2407336)

Ho, E.S.L. , Komura, T., Ramamoorthy, S. and Vijayakumar, S. (2010) Controlling Humanoid Robots in Topology Coordinates. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei, Taiwan, 18-22 October 2010, pp. 178-182. ISBN 9781424466764 (doi: 10.1109/IROS.2010.5652787)

Ho, E.S.L. and Komura, T. (2009) Planning Tangling Motions for Humanoids. In: 2007 7th IEEE-RAS International Conference on Humanoid Robots, Pittsburgh, PA, USA, 29 November - 1 December 2007, pp. 507-512. ISBN 9781424418619 (doi: 10.1109/ICHR.2007.4813918)

Ho, E. S.L. and Komura, T. (2007) Wrestle Alone : Creating Tangled Motions of Multiple Avatars from Individually Captured Motions. In: 15th Pacific Conference on Computer Graphics and Applications (PG'07), Maui, HI, USA, 29 October- 2 November 2007, ISBN 9780769530093 (doi: 10.1109/pg.2007.54)

Ho, E.S.L. , Komura, T. and Lau, R.W.H. (2005) Computing Inverse Kinematics with Linear Programming. In: VRST05: The ACM Symposium on Virtual Reality Software and Technology 2005, Monterey, CA, USA, 7 - 9 November 2005, pp. 163-166. ISBN 1595930981 (doi: 10.1145/1101616.1101651)

This list was generated on Fri Jul 12 07:07:41 2024 BST.

Grants

Turing Network Development Award, EPSRC / The Alan Turing Institute, Award Lead and Proposal Lead, 2022

 

D-FOCUS: Drone-FOrmation Control for countering future Unmanned aerial Systems, The Ministry of Defence (DASA) - Defence and Security Accelerator (Ref: DSTLX-1000140725), PI, 2019-2020

 

Autonomous Monitoring for Patients and Older People using Smart Environments with Sensor Fusion, Royal Society Yusuf Hamied International Exchange Award (Ref: IES/R1/191147), PI, 2019-2022

 

Deep Learning in Computer Graphics and Virtual Reality, NVIDIA GPU Grant, PI, 2018

 

Shoes2Run - Wearable Technology, Creative Fuse North East, Co-Investigator (PI: Shoes2Run Limited, industrial partner), 2018

 

A Multi-resolution Spatial Relation based Representation for Close Character Interactions Analysis and Synthesis, RGC General Research Fund (RGC/HKBU210813), PI, 2013-2016

 

Modelling Human-Object Interactions based on Spatial Relations for Robust Action Recognition, NSFC Young Scientists Fund (Ref: 61302176), PI, 2013-2016

 

Modelling Temporal Structure for Robust and Efficient Human Action Recognition, HKBU Faculty Research Grant (FRG2/14-15/105), PI, 2015-2016

 

Monitoring Posture for Workplace Health and Safety with A Depth Camera, HKBU Faculty Research Grant (FRG2/13-14/092), PI, 2014-2015

 

Research on Efficient Multi-Character Motion Adaptation Based on A Multi-resolution Hierarchical Model for Spacetime Optimization, HKBU Faculty Research Grant (FRG2/12-13/078), PI, 2013-2014

 

Synthesizing Physically Valid Close Interactions for Controlling Humanoid Characters and Robots, HKBU Faculty Research Grant (FRG1/12-13/055), PI, 2013-2014

Supervision

I am currently looking for PhD students who are interested in Computer Vision, Computer Graphics and Machine Learning. Two potential project directions are listed below and I am open to other relevant topics as well. The candidate is expected to have strong programming skills, some prior experience in machine learning and visual computing (computer vision and/or computer graphics), and good English communication skills. Please contact me (Shu-Lim.Ho@glasgow.ac.uk) for further information.

 

1. Modelling Close Human-Human and Human-Object Interactions for Human Digitization

The aim of this project is to propose new methods for modelling the close interactions between human-human and human-object. Such an approach can be used for tackling problems in a wide range of tasks, including scene understanding, pose estimation and 3D human reconstruction in Computer Vision, as well as synthesizing interactive contents in Computer Graphics and Virtual Reality.

Analysing the relationships between human-human and human-object from images plays an important role in providing contextual information in addition to the low-level features (such as key points on the human and object). Although encouraging results are demonstrated by using data-driven and deep learning techniques in recent years, handling scenes which contains close interactions between human and objects is still a challenging task since the key entities (human(s) and object(s)) are usually partially occluded and resulted in low-quality input data. In this research, we will bridge this gap by utilising prior knowledge in close interactions to better model the human-human and human-object interactions.

The supervisory team has extensive experience in this area and the details of the relevant publications can be found here: http://www.edho.net/projects/close_interaction/

 

2. Early Prediction of Cerebral Palsy using Machine Learning and Computer Vision with Multimodal Data

The aim of this project is to propose new machine learning based framework for detecting abnormal infant movement from RGB videos. In particular, this project will focus on modelling the multimodal data collected from our NHS partners to improve the robustness and accuracy of the early prediction of Cerebral Palsy (CP).

CP is the collective term given to a group lifelong neurological conditions and the most prevalent physical disability found in children, with 2.11 diagnoses per 1000 live births. There is also an increased prevalence of CP in infants born prematurely, with 32.4 diagnoses per 1000 infants born very preterm (28-32 weeks gestation), and 70.6 diagnoses per 1000 infants born extremely preterm (<28 weeks gestation).

As such, the early diagnosis of CP is an ongoing area of multidisciplinary research, as it has the potential to allow for early intervention clinical care. However, early diagnosis can be difficult and time-consuming. Diagnostic tools such as the General Movements Assessment (GMA), have produced some very promising results. However, the prospect of automating these processes may improve the accessibility of the assessment and also enhance the understanding of the movement development of infants.

The supervisory team has extensive experience in this area and the details of the relevant publications can be found here: http://www.edho.net/projects/babies/

 

 

  • Dong, Zeyu
    Vision-based 3D Flow and Occupancy Prediction
  • Fan, Shiyu
    Reconstructing Physcially Feasible 3D Human Model in Close Human-Human and Human-Object Interactions from Monocular Images
  • Luo, Zeqi
    Human Motion Analysis for Early Screening of Cerebral Palsy
  • Sun, Chenxiang
    Early Prediction of Cerebral Palsy using Deep Learning and Computer Vision with Multimodal Data
  • Xie, Yuxuan
    Pedestrian Interaction Modelling via Ego-centric View for Autonomous Driving
  • Xu, Wenning
    Modelling Two-person and Human-object Close Interactions
  • Zhang, Xi
    Generative Multi-modal BioMedical Natural Language Modelling

Externally supervised students:

  • Manli Zhu, Human action recognition with graph convolution (PhD student since 2020)

  • Shaun Lillie, Enhancing the learning experience of autistic students in Higher Education using AI and VR (PhD student since 2020)

  • Luca Crosato, Computer vision for autonomous vehicles (PhD student since 2020)

 

Alumni:

  • Dr. Kevin McCay, Automated early prediction of cerebral palsy: interpretable pose-based assessment for the identification of abnormal infant movements (Graduated in 2022)

  • Dr. Daniel Organisciak, Neural attention mechanisms for robust and interpretable feature representation learning (Graduated in 2022, co-supervised)

  • Dr. Dimitrios Sakkos, Video foreground segmentation with deep learning (Graduated in 2020)

  • Dr. Jingtian Zhang, Learning discriminative features for human motion understanding (Graduated in 2020, Co-supervised)

  • Dr. Yijun Shen, Human motion analysis and synthesis in computer graphics (Graduated in 2019, Co-supervised)

Professional activities & recognition

Editorial boards

  • 2023 - 2026: Computer Graphics Forum

Additional information

My Personal Webpage: http://www.edho.net