Multiple-Object-Tracking

Tracking body parts in behaving animals, extracting fluorescence signals from cells embedded in deforming tissue, and analyzing cell migration patterns during development all require tracking objects with partially correlated motion. As dataset sizes …

We used different image filters (gaussian filters, erosion and dilation), background subtraction methods (frame differences, gaussian mixture model and adaptive background learning), vehicle detection methods (edge analysis, haarcascade training and deformable parts model), and object tracking methods (optical flow pattern) to reach a high accuracy. Done in Paaydar team (I was team leader in this project) with M. Razeghi, E. Tavakkoli and A. Arabzadeh. Implemented in C++ using OpenCV library.