SiamBOMB: A Real-time AI-based System for Home-cage Animal Tracking, Segmentation and Behavioral Analysis
We develop an AI-based multi-species tracking and segmentation system, SiamBOMB, for real-time and automatic home-cage animal behavioral analysis.
Xi Chen*, Hao Zhai*, Danqian Liu, Weifu Li, Chaoyue Ding, Qiwei Xie, Hua Han
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
School of Automation and Electrical Engineering, University of Science and Technology Beijing
Howard Hughes Medical Institute, University of California
College of Science, Huazhong Agricultural University
Center of Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences
Abstract
Biologists often need to handle numerous video-based home-cage animal behavior analysis tasks that require massive workloads. Therefore, we develop an AI-based multi-species tracking and segmentation system, SiamBOMB, for real-time and automatic home-cage animal behavioral analysis. In this system, a background-enhanced Siamese-based network with replaceable modular design ensures the flexibility and generalizability of the system, and a user-friendly interface makes it convenient to use for biologists. This real-time AI system will effectively reduce the burden on biologists.
Citation
Chen X, Zhai H, Liu D, Li W, Ding C, Xie Q, Han H (2021). SiamBOMB: a real-time AI-based system for home-cage animal tracking, segmentation and behavioral analysis. In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 5300-5302. https://doi.org/10.24963/ijcai.2020/776.