Minimum Cost Multi-Way Data Association for Optimizing Multitarget Tracking of Interacting Objects

• Published in: IEEE transactions on pattern analysis and machine intelligence Vol. 37; no. 3; pp. 611 - 624
• Main Authors: Park, Chiwoo, Woehl, Taylor J., Evans, James E., Browning, Nigel D.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2015
• Subjects: Algorithms; Humans; Image Processing, Computer-Assisted - methods; Linear programming; Microscopy, Electron; Microscopy, Video; Models, Theoretical; Nanoparticles; Pattern Recognition, Automated - methods; Radar tracking; Target tracking; Time measurement; Trajectory; Video sequences; Visualization; decomposition; binary integer programming; Data association; lagrange dual relaxation
• ISSN: 0162-8828; 1939-3539; 2160-9292
• DOI: 10.1109/TPAMI.2014.2346202

This paper presents a general formulation for a minimum cost data association problem which associates data features via one-to-one, m-to-one and one-to-n links with minimum total cost of the links. A motivating example is a problem of tracking multiple interacting nanoparticles imaged on video frames, where particles can aggregate into one particle or a particle can be split into multiple particles. Many existing multitarget tracking methods are capable of tracking non-interacting targets or tracking interacting targets of restricted degrees of interactions. The proposed formulation solves a multitarget tracking problem for general degrees of inter-object interactions. The formulation is in the form of a binary integer programming problem. We propose a polynomial time solution approach that can obtain a good relaxation solution of the binary integer programming, so the approach can be applied for multitarget tracking problems of a moderate size (for hundreds of targets over tens of time frames). The resulting solution is always integral and obtains a better duality gap than the simple linear relaxation solution of the corresponding problem. The proposed method was validated through applications to simulated multitarget tracking problems and a real multitarget tracking problem.