Name
Title | ||
|---|---|---|
Computer Graphics Meets Estimation Theory: Parameter Estimation Lower Bounds For Plenoptic Imaging Systems |
Abstract | ||
|---|---|---|
This work focuses on assessing the information-theoretic limits of parameter estimation in plenoptic imaging systems, which are capable of providing substantially more information about a given scene than conventional cameras. We present a framework to compute lower bounds for parameter estimation from noisy plenoptic observations, and our particular focus is on indirect imaging problems, where the observations do not contain line-of-sight (LOS) information about the parameter(s) of interest. Using computer graphics rendering software to synthesize the (often complicated) dependence among parameter(s) of interest and observations, we numerically evaluate the Hammersley-Chapman-Robbins bound to establish fundamental lower limits on the variance of any unbiased estimators of the unknown parameters. We demonstrate the utility of our proposed framework on a few canonical estimation tasks. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IEEECONF44664.2019.9048801 | CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS |
Keywords | DocType | ISSN |
Plenoptic Imaging, Cramer-Rao bound, Hammersley-Chapman-Robbins bound | Conference | 1058-6393 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Abhinav V. Sambasivan | 1 | 0 | 1.69 |
| Richard G. Paxman | 2 | 0 | 0.34 |
| Jarvis Haupt | 3 | 1339 | 131.86 |