Automated Tracking System for Identification of Tagged Mice for Automatic Social Behavior Analysis

Fabio Marcuccio, Alena Savonenko, Ralph Etienne-Cummings

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Monitoring mice social behaviors is extremely important for neurobehavioral analysis. State-of-the-art monitoring systems still require human handling for phenotype characterization with high cost and low standardization. Mice tracking and identity preservation represent the first step for phenotyping. This paper focuses on a new automated tracking system able to identify mice and keep their identities frame by frame, laying the groundwork for automatic social behavior analysis. Our system achieves more than 80% accuracy on metal ear tags identification on one-minute long videos recorded at 30 fps.

Original languageEnglish (US)
Title of host publication2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538636039
DOIs
StatePublished - Dec 20 2018
Event2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Cleveland, United States
Duration: Oct 17 2018Oct 19 2018

Other

Other2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018
CountryUnited States
CityCleveland
Period10/17/1810/19/18

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Health Informatics
  • Instrumentation
  • Signal Processing
  • Biomedical Engineering

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  • Cite this

    Marcuccio, F., Savonenko, A., & Etienne-Cummings, R. (2018). Automated Tracking System for Identification of Tagged Mice for Automatic Social Behavior Analysis. In 2018 IEEE Biomedical Circuits and Systems Conference, BioCAS 2018 - Proceedings [8584712] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIOCAS.2018.8584712