Name
Abstract | ||
|---|---|---|
We consider the problem of estimating the path taken by an object in a road network from sparse, noisy position measurements. Path estimation is posed in a Bayesian framework which allows the incorporation of prior information about vehicle movements. A carefully designed importance sampler is used to approximate the posterior path probabilities. The algorithm is demonstrated on simulated data. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP) | path estimation, Bayesian estimation, Monte Carlo approximation |
Field | DocType | ISSN |
Pattern recognition,Computer science,Artificial intelligence,Bayesian probability | Conference | 1520-6149 |
Citations | PageRank | References |
1 | 0.37 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark R. Morelande | 1 | 6 | 1.86 |
| Matt Duckham | 2 | 962 | 62.78 |
| Allison Kealy | 3 | 70 | 12.14 |
| Jonathan Legg | 4 | 1 | 0.37 |