Track Fast-Moving Tiny Flies by Adaptive LBP Feature and Cascaded Data Association
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.
M. Li et al., "Track Fast-Moving Tiny Flies by Adaptive LBP Feature and Cascaded Data Association," Proceedings of the 20th IEEE International Conference on Image Processing (2013, Melbourne, VIC, Australia), pp. 1172-1176, Institute of Electrical and Electronics Engineers (IEEE), Sep 2013.
The definitive version is available at https://doi.org/10.1109/ICIP.2013.6738242
20th IEEE International Conference on Image Processing (2013: Sep. 15-18, Melbourne, VIC, Australia)
Engineering Management and Systems Engineering
Keywords and Phrases
Multiple Object Tracking; Adaptive Local Binary Pattern Feature; Cascaded Data Association
International Standard Serial Number (ISSN)
Article - Conference proceedings
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