Dr. Cai is a Lecturer in the Department of Computer Science, Loughborough University. He previously worked as a Research Associate at the University of Portsmouth (2016-2018), Loughborough University (2018-2019) and Imperial College London (2019). His research interests include Computer Vision, Robotics and the application of Convolution Neural Networks in these areas.


  • PI, Understanding Human Intention for Robots (The Royal Society, RGS\R1\231286, 2023 -2024, £48k)
  • PI, Unconstrained Gaze Estimation for Effective Human-robot Interaction (Royal Society International Exchanges, IEC\NSFC\211032, 2022-2024, £10k)
  • PI, Sport and Exercise Beacon seedcorn funding (Loughborough University, 2021, £2500)
  • Co-I, KTP: Loughborough University and MoA Technology Limited (2023-2025, £186k)
  • Co-I, something old, something new: unlock understanding of archived plant specimens (2022-2023, £19k)

Research areas

  • Robot Vision
  • Eye Tracking & Gaze Estimation
  • Face Expression Recognition
  • Motion Recognition
  • Object Detection & Segmentation

Featured publications

  • Cai, H., Jiang, L., Liu, B., Deng, Y. and Meng, Q., 2019. Assembling convolution neural networks for automatic viewing transformation. IEEE Transactions on Industrial Informatics.
  • Liu, B., Cai, H., Ju, Z. and Liu, H., 2019. RGB-D sensing based human action and interaction analysis: A survey. Pattern Recognition94, pp.1-12.
  • Liu, B., Cai, H., Ju, Z. and Liu, H., 2019. Multi-stage Adaptive Regression for Online Activity Recognition. Pattern Recognition, p.107053.
  • Cao, H.L., Esteban, P., Bartlett, M., Baxter, P.E., Belpaeme, T., Billing, E., Cai, H., Coeckelbergh, M., Costescu, C. and David, D., 2019. Robot-enhanced therapy: development and validation of a supervised autonomous robotic system for autism spectrum disorders therapy. IEEE Robotics and Automation Magazine.
  • Cai, H., Fang, Y., Ju, Z., Costescu, C., David, D., Billing, E., Ziemke, T., Thill, S., Belpaeme, T., Vanderborght, B. and Vernon, D., 2018. Sensing-enhanced therapy system for assessing children with autism spectrum disorders: a feasibility study. IEEE Sensors Journal19(4), pp.1508-1518.
  • Cai, H., Liu, B., Ju, Z., Thill, S., Belpaeme, T., Vanderborght, B. and Liu, H., 2018, September. Accurate Eye Center Localization via Hierarchical Adaptive Convolution. In British Machine Vision Conference (BMVC) (p. 284).
  • Zhou, X., Li, J., Chen, S., Cai, H. and Liu, H., 2018. Multiple perspective object tracking via context-aware correlation filter. IEEE Access6, pp.43262-43273.
  • Esteban, P.G., Baxter, P., Belpaeme, T., Billing, E., Cai, H., Cao, H.L., Coeckelbergh, M., Costescu, C., David, D., De Beir, A. and Fang, Y., 2017. How to build a supervised autonomous system for robot-enhanced therapy for children with autism spectrum disorder. Paladyn, Journal of Behavioral Robotics8(1), pp.18-38.
  • Liao, Y., Sun, Y., Li, G., Kong, J., Jiang, G., Jiang, D., Cai, H., Ju, Z., Yu, H. and Liu, H., 2017. Simultaneous calibration: a joint optimization approach for multiple kinect and external cameras. Sensors17(7), p.1491.
  • Zhou, X., Cai, H., Li, Y. and Liu, H., 2017, May. Two-eye model-based gaze estimation from a Kinect sensor. In IEEE International Conference on Robotics and Automation (ICRA) (pp. 1646-1653).
  • Cai, H., Lee, D., Joonkoo, H., Fang, Y., Li, S. and Liu, H., 2017, October. Embedded vision based automotive interior intrusion detection system. In IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2909-2914). IEEE.
  • Liu, B., Cai, H., Ji, X. and Liu, H., 2017, September. Human-human interaction recognition based on spatial and motion trend feature. In IEEE International Conference on Image Processing (ICIP) (pp. 4547-4551).
  • Cai, H., Yu, H., Zhou, X. and Liu, H., 2016, August. Robust gaze estimation via normalized iris center-eye corner vector. In International conference on intelligent robotics and applications (ICIRA) (pp. 300-309).
  • Cai, H., Liu, B., Zhang, J., Chen, S. and Liu, H., 2015. Visual focus of attention estimation using eye center localization. IEEE Systems Journal11(3), pp.1320-1325.
  • Cai, H., Zhou, X., Yu, H. and Liu, H., 2015, November. Gaze estimation driven solution for interacting children with asd. In International Symposium on Micro-NanoMechatronics and Human Science (MHS) (pp. 1-6).
  • Cai, H., Yu, H., Yao, C., Chen, S. and Liu, H., 2015. Convolution-based means of gradient for fast eye center localization. In International Conference on Machine Learning and Cybernetics (ICMLC) (Vol. 2, pp. 759-764).