Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
MCMC-Based Particle Filtering for Tracking a Variable Number of Interacting Targets
IEEE Transactions on Pattern Analysis and Machine Intelligence
Floor Fields for Tracking in High Density Crowd Scenes
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part II
Multiple hypothesis tracking in microscopy images
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Microscope Image Processing
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The tracking of cell populations in time-lapse microscopy images enables high-throughput spatiotemporal measurements of cell dynamics. In this paper, we present a new algorithm to simultaneously track many cells in crowded areas. The algorithm runs in real time and deals with thousands of cells. The main contribution of this paper is that the algorithm is able to maintain the spatiotemporal consistency of the tracks in crowded areas, even when the temporal resolution is coarse. We validate our approach in terms of its ability to track yeast cells.