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Track fast-moving tiny flies by adaptive LBP feature and cascaded data association

  • Missouri University of Science and Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Studying the behavior of fruit flies that mimic normal animal motivations can inform us about the molecular mechanisms and biochemical pathways. We build a glass chamber to house flies and record their behaviors in video frame sequences. Due to the challenges of low image contrast, small object size and fast object motion, we propose an adaptive Local Binary Pattern (LBP) feature to detect flies and develop a cascaded data association approach with fine-to-coarse gating region control to track flies in the spatio-temporal domain. Our approach is validated on two long video sequences with very good performance, showing its potential to enable automated characterization of biological processes.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings
PublisherIEEE Computer Society
Pages1172-1176
Number of pages5
ISBN (Print)9781479923410
DOIs
StatePublished - 2013
Event2013 20th IEEE International Conference on Image Processing, ICIP 2013 - Melbourne, VIC, Australia
Duration: Sep 15 2013Sep 18 2013

Publication series

Name2013 IEEE International Conference on Image Processing, ICIP 2013 - Proceedings

Conference

Conference2013 20th IEEE International Conference on Image Processing, ICIP 2013
Country/TerritoryAustralia
CityMelbourne, VIC
Period09/15/1309/18/13

Keywords

  • Multiple object tracking
  • adaptive local binary pattern feature
  • cascaded data association

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