Hongxin Wang received his PhD in computer science from the University of Lincoln in 2020. Following a secondment under the STEP2DYNA project, Dr Wang carried out a further secondment under the ULTRACEPT project from April 2020 to April 2021 at partner Guangzhou University. Here, he undertook research contributing to work packages 1 and 2. Dr Wang’s ULTRACEPT contributions have involved directing the research into computational modelling of motion vision neural systems for small target motion detection.
University of Lincoln’s Experienced Researcher Dr Hongxin Wang recently completed a 12 month secondment at ULTRACEPT project partner Guangzhou University in China. The project is funded by the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skolodowska-Curie grant agreement. Dr Wang visited Guangzhou from April 2020 to April 2021 and contributed to Work Package 1 and 2.
Dr Wang reflects on what he has achieved during secondment
Monitoring moving objects against complex natural backgrounds is a huge challenge to future robotic vision systems, and even more so when attempting to detect small targets only a few pixels in size, for example, an unmanned aerial vehicle (UAV) or a bird in the distance, as shown in Fig. 1. Surprisingly, insects are quite apt at searching for mates and tracking prey, which appears as small dim speckles in the visual field. The exquisite sensitivity of insects for small target motion comes from a class of specific neurons called small target motion detectors (STMDs). Building a quantitative STMD model is the first step for not only further understanding the biological visual system but also providing robust and economic solutions of small target detection for an artificial vision system.
During this twelve-month secondment, I continued my previous work on modeling insects’ visual systems for small target detection and have made great progress. Specifically, we proposed a STMD-based model with time-delay feedback to achieve superior detection performance for fast-moving small targets, whilst significantly suppressing background false positive movements which display lower velocities. This work has been submitted to IEEE Transactions on Neural Networks and Learning Systems and is currently under review. In addition, we developed an attention-prediction guided visual system to overcome the heavy dependency of the existing models on target contrast to background, as illustrated in Fig. 2. The paper presenting this work has been completed and will be submitted to IEEE Transactions on Cybernetics.
During my 12 month secondment at Guangzhou University, I obtained inspiration and mathematical theory support from Professor Jigen Peng to design the STMD-based visual systems. We organized a seminar every week to discuss the latest biological findings, explore effective neural modeling methods, and develop specialised mathematical theory for bioinspired motion detection. Significant progress was made under the help of Professor Jigen Peng.
The secondment has also provided me with an opportunity to improve my mathematical ability with support from Professor Peng. Strong mathematical ability helps me better describe the insects’ visual systems, and build robust neural models for small target motion detection. In addition, I established a deep friendship with Professor Peng and my colleagues at Guangzhou University, which is providing me a basis for future research collaborations. Lastly, I introduced our research to colleagues during the discussion, which may attract their attention to our research field and finally boost the development of neural system modelling.
The secondment has been an excellent experience for me and provided me the opportunity to collaborate with my project colleagues. Thank you for the support from the ULTRACEPT project which benefited me a lot.