Name
Title | ||
|---|---|---|
A Novel Multi-cell Multi-Bernoulli Tracking Method Using Local Fractal Feature Estimation. |
Abstract | ||
|---|---|---|
A novel multi-cell tracking method based on multi-Bernoulli filter using local fractal feature estimation is proposed in this paper. The Hurst coefficient estimated by the rescaled range analysis method is considered as the local fractal feature. The local fractal feature can offer two advantages for multi-Bernoulli filter. The input of filter is the Hurst coefficient image, the direct effect is that observation can be modeled simply. And the likelihood function can be computed easily using this feature. Experiment results show that our proposed method could achieve an accurate and joint estimate of the number of cells and their individual states especially in the case of the number of cell population varying and the cellular morphology changing. And it shows equivalent accuracy against other tracking methods. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-61833_33 | ADVANCES IN SWARM INTELLIGENCE, ICSI 2017, PT II |
Keywords | Field | DocType |
Multi-cell tracking,Multi-Bernoulli filter,Local fractal feature,Hurst coefficient,Rescaled range analysis | Population,Mathematical optimization,Likelihood function,Cellular Morphology,Computer science,Fractal,Hurst exponent,Algorithm,Rescaled range,Bernoulli's principle | Conference |
Volume | ISSN | Citations |
10386 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 13 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jihong Zhu | 1 | 64 | 29.14 |
| Benlian Xu | 2 | 81 | 20.96 |
| Mingli Lu | 3 | 36 | 11.58 |
| Jian Shi | 4 | 18 | 4.78 |
| Peiyi Zhu | 5 | 2 | 1.39 |