Name
Title | ||
|---|---|---|
Fluorescence Lidar System Modeling For Underwater Object Recognition Performance Evaluation |
Abstract | ||
|---|---|---|
This paper presents an end-to-end fluorescence LIDAR system modeling approach for predicting the performance of underwater object recognition. The overall LIDAR system chain is modeled, starting from LIDAR pulse generation up to collection and processing of the inelastic backscattering signal returned by the underwater object. A comprehensive simulator to reproduce in-water LIDAR propagation phenomena is included in the model. The proposed approach is capable of predicting underwater object recognition performance under various different fluorescence LIDAR system characteristics as well as viewing geometries and environmental conditions. Experimental results featuring immersion of an object in Case 1 and Case 2 waters show the potential of the proposed modeling approach. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | Fluorescence LIDAR, underwater object detection and recognition, LIDAR simulator |
Field | DocType | ISSN |
Computer vision,Computer science,Remote sensing,Backscatter,Lidar,Systems modeling,Artificial intelligence,Laser beams,Underwater,Cognitive neuroscience of visual object recognition | Conference | 2153-6996 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Stefania Matteoli | 1 | 152 | 18.05 |
| Laura Zotta | 2 | 3 | 1.23 |
| Marco Diani | 3 | 261 | 30.99 |
| Giovanni Corsini | 4 | 299 | 40.26 |