Corpus ID: 174801444

Detection and Tracking of Multiple Mice Using Part Proposal Networks

@article{Jiang2019DetectionAT,
  title={Detection and Tracking of Multiple Mice Using Part Proposal Networks},
  author={Zheheng Jiang and Zhihua Liu and Long Chen and Lei Tong and Xiangrong Zhang and Xiangyuan Lan and Danny Crookes and Ming-Hsuan Yang and Huiyu Zhou},
  journal={ArXiv},
  year={2019},
  volume={abs/1906.02831}
}
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… Expand
2 Citations
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Deep learning tools for the measurement of animal behavior in neuroscience
TLDR
It is envisioned that the fast-paced development of new deep learning tools will rapidly change the landscape of realizable real-world neuroscience. Expand

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