Name
Abstract | ||
|---|---|---|
Laser Vibrometry is an exciting new sensor technology that promises to improve automatic target recognition (ATR) performance. Sensors such as Micro-Laser Interferometer Doppler (MLID) measure minute vibrations on the surface of an object from a large standoff distance. In this paper, we demonstrate a baseline ATR algorithm designed for vibrometry data that can reliably recognize military vehicles when trained and tested on similar operating conditions. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ICPR.2002.1047842 | Pattern Recognition, 2002. Proceedings. 16th International Conference |
Keywords | Field | DocType |
feature extraction,measurement by laser beam,object recognition,pattern classification,vibration measurement,automatic target recognition,feature extraction,laser vibrometry,micro-laser interferometer Doppler,military ground vehicles,pattern classification,sensor,vibration spectral signature | Computer vision,Algorithm design,Automatic target recognition,Pattern recognition,Computer science,Interferometry,Feature extraction,Laser,Artificial intelligence,Vibration,Doppler effect,Cognitive neuroscience of visual object recognition | Conference |
Volume | ISSN | ISBN |
3 | 1051-4651 | 0-7695-1695-X |
Citations | PageRank | References |
2 | 0.40 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark R. Stevens | 1 | 75 | 8.93 |
| Magnus Snorrason | 2 | 15 | 3.56 |
| Daniel Petrovich | 3 | 2 | 0.40 |