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Detection and Tracking of Multiple Mice Using Part Proposal Networks

创建时间:  2019/06/26  王智渊   浏览次数:   返回

报告英文题目:Detection and Tracking of Multiple Mice Using Part Proposal Networks

报告中文题目:采用部分生成网络检测和跟踪多个小鼠

报告人: Dr. Huiyu (Joe) Zhou, Reader (University of Leicester, UK)

           周挥宇副教授(英国莱斯特大学)

报告时间:  2019年6月27日(周四)下午3:00点

报告地点:  1066vip威尼斯宝山校区东区机自大楼702B室

报告摘要:

The study of mouse social behaviours has been increasingly undertaken in neuroscience research. However, automated quantification of mouse behaviours from the videos of interacting mice is still a challenging problem, where object tracking plays a key role in locating mice in their living spaces. Artificial markers are often applied for multiple mice tracking, which are intrusive and consequently interfere with the movements of mice in a dynamic environment. In this paper, we propose a novel method to continuously track several mice and individual parts without requiring any specific tagging. Firstly, we propose an efficient and robust deep learning based mouse part detection scheme to generate part candidates. Subsequently, we propose a novel Bayesian Integer Linear Programming Model that jointly assigns the part candidates to individual targets with necessary geometric constraints whilst establishing pair-wise association between the detected parts. There is no publicly available dataset in the research community that provides a quantitative test-bed for the part detection and tracking of multiple mice, and we here introduce a new challenging Multi-Mice PartsTrack dataset that is made of complex behaviours and actions. Finally, we evaluate our proposed approach against several baselines on our new datasets, where the results show that our method outperforms the other state-of-the-art approaches in terms of accuracy.

报告人简介:

Dr. Huiyu Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China, and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom. Dr. Zhou currently is a Reader at Department of Informatics, University of Leicester, United Kingdom. He has published over 200 peer-reviewed papers in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", “ICPRAM 2016 Best Paper Award” and was nominated for “ICPRAM 2017 Best Student Paper Award” and "MBEC 2006 Nightingale Prize". Four of his papers recently published by Elsevier were ranked as the ScienceDirect Top 25 Articles. Dr. Zhou serves as the Editor-in-Chief of Recent Advances in Electrical & Electronic Engineering and Associate Editor of "IEEE Transaction on Human-Machine Systems", and is on the Editorial Boards of several refereed journals. He is one of the Technical Committee of “Information Assurance & Intelligent Multimedia-Mobile Communication in IEEE SMC Society”, “Robotics Task Force” and “Biometrics Task Force” of the Intelligent Systems Applications Technical Committee, IEEE Computational Intelligence Society. He has given over 50 invited talks at international conferences, industry and universities, and has served as a chair for 30 international conferences and workshops. His research work has been or is being supported by UK EPSRC, MRC, EU, Royal Society, Leverhulme Trust, Puffin Trust, Alzheimer’s Research UK, Invest NI and industry.

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