title: Tri-track: free software for large-scale particle tracking.
abstract: The ability to correctly track objects in time-lapse sequences is important in many applications of microscopy. Individual object motions typically display a level of dynamic regularity reflecting the existence of an underlying physics or biology. Best results are obtained when this local information is exploited. Additionally, if the particle number is known to be approximately constant, a large number of tracking scenarios may be rejected on the basis that they are not compatible with a known maximum particle velocity. This represents information of a global nature, which should ideally be exploited too. Some time ago, we devised an efficient algorithm that exploited both types of information. The tracking task was reduced to a max-flow min-cost problem instance through a novel graph structure that comprised vertices representing objects from three consecutive image frames. The algorithm is explained here for the first time. A user-friendly implementation is provided, and the specific relaxation mechanism responsible for the method's effectiveness is uncovered. The software is particularly competitive for complex dynamics such as dense antiparallel flows, or in situations where object displacements are considerable. As an application, we characterize a remarkable vortex structure formed by bacteria engaged in interstitial motility.
authors: CSIRO, Division of Mathematics, Informatics, and Statistics, Locked Bag 17, North Ryde NSW 1670, Australia.
authors: Pascal
authors: P
authors: Vallotton
authors: Sandra
authors: S
authors: Olivier
mesh_terms: D000465:Algorithms; D058948:Cell Tracking / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D009068:Movement; D010363:Pattern Recognition, Automated; D011550:Pseudomonas aeruginosa / Q000502:physiology*; D012984:Software / Q000191:economics