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.