Track Fast-Moving Tiny Flies by Adaptive LBP Feature and Cascaded Data Association

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.

Meeting Name

20th IEEE International Conference on Image Processing (2013: Sep. 15-18, Melbourne, VIC, Australia)

Department(s)

Computer Science

Second Department

Biological Sciences

Third Department

Engineering Management and Systems Engineering

Keywords and Phrases

Multiple Object Tracking; Adaptive Local Binary Pattern Feature; Cascaded Data Association

International Standard Serial Number (ISSN)

1522-4880

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2013 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Sep 2013

Link to Full Text

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