Name
Abstract | ||
|---|---|---|
Multiple hypothesis tracking (MHT) is a preferred technique for solving the data association problem in modern multiple targets tracking systems. However its computational cost is generally considered prohibitive for tracking numerous objects in cluttered environments due to numerous targets and spurious measurements. We present in this paper a new MHT formulation in which target perceivability is modeled whereby automatic early track termination and false measurements exclusion reduce the problem complexity and improve the method robustness to clutter. Moreover we propose a MHT implementation exploiting the tree structure of the potential tracks to take full advantages of recent parallel computing technologies. We provide experimental results showing that both the track model and algorithmic design make the algorithm fast and robust even in highly complex situations such as tracking numerous particles in fluorescent microscopy images. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICIP.2009.5414278 | Image Processing |
Keywords | Field | DocType |
computational complexity,hidden Markov models,image fusion,parallel processing,target tracking,trees (mathematics),automatic early track termination,computational cost,data association problem,false measurements exclusion,fluorescent microscopy images,hidden Markov model,multiple hypothesis tracking,multiple targets tracking system,parallel computing technology,problem complexity,target perceivability,tree structure,Hidden Markov Model,Multiple Hypothesis Tracking (MHT),Particle tracking,bioimaging | Computer vision,Algorithm design,Clutter,Computer science,Tracking system,Robustness (computer science),Tree structure,Artificial intelligence,Hidden Markov model,Spurious relationship,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
1522-4880 E-ISBN : 978-1-4244-5655-0 | 978-1-4244-5655-0 | 7 |
PageRank | References | Authors |
0.82 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nicolas Chenouard | 1 | 134 | 11.04 |
| Isabelle Bloch | 2 | 2123 | 170.75 |
| Olivo-Marin, J.-C. | 3 | 63 | 8.68 |