Multiple Drosophila tracking with behavior classification

Pudith Sirigrivatanawong, Koichi Hashimoto

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

1 Citation (Scopus)

Abstract

Behavior changes in model organisms provides information on how the organisms react to the environment or given stimuli. This knowledge helps scientist understand the process of life that can be used in term of medicine or disease threatening. In order to observe the behavior changes, computer vision is considered to be a superior tool for locomotion analysis as it can provide more precise and time efficient data in comparison with manual measurement. Moreover, a classification tool that can utilize the result from machine vision is also required. In this study, the usage of Drosophila tracking tool and behavior classifier is introduced. The fly tracking system can efficiently detect and track flies inside a closed arena. The result, which is in form of locomotion data such as position and velocity, is processed with a classifier tool to generate behavior label to each fly throughout the input video. As a result, the overall process not only provides insightful data, but also reduces time consumption to deal with the behavior analysis of Drosophila in comparison to the same process done manually.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1041-1046
Number of pages6
ISBN (Electronic)9781509067572
DOIs
Publication statusPublished - 2017 Aug 23
Event14th IEEE International Conference on Mechatronics and Automation, ICMA 2017 - Takamatsu, Japan
Duration: 2017 Aug 62017 Aug 9

Publication series

Name2017 IEEE International Conference on Mechatronics and Automation, ICMA 2017

Other

Other14th IEEE International Conference on Mechatronics and Automation, ICMA 2017
CountryJapan
CityTakamatsu
Period17/8/617/8/9

Keywords

  • Computer vision
  • Image processing
  • Random forest
  • Tracking

ASJC Scopus subject areas

  • Control and Optimization
  • Instrumentation
  • Artificial Intelligence
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

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