DMCA
Daisy: An efficient dense descriptor applied to wide baseline stereo (2010)
| Venue: | IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE |
| Citations: | 126 - 13 self |
BibTeX
@ARTICLE{Tola10daisy:an,
author = {Engin Tola and Vincent Lepetit and Pascal Fua},
title = {Daisy: An efficient dense descriptor applied to wide baseline stereo},
journal = {IEEE TRANS. PATTERN ANALYSIS AND MACHINE INTELLIGENCE},
year = {2010},
volume = {32},
number = {5}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
In this paper, we introduce a local image descriptor, DAISY, which is very efficient to compute densely. We also present an EM-based algorithm to compute dense depth and occlusion maps from wide-baseline image pairs using this descriptor. This yields much better results in wide-baseline situations than the pixel and correlation-based algorithms that are commonly used in narrowbaseline stereo. Also, using a descriptor makes our algorithm robust against many photometric and geometric transformations. Our descriptor is inspired from earlier ones such as SIFT and GLOH but can be computed much faster for our purposes. Unlike SURF, which can also be computed efficiently at every pixel, it does not introduce artifacts that degrade the matching performance when used densely. It is important to note that our approach is the first algorithm that attempts to estimate dense depth maps from wide-baseline image pairs, and we show that it is a good one at that with many experiments for depth estimation accuracy, occlusion detection, and comparing it against other descriptors on laser-scanned ground truth scenes. We also tested our approach on a variety of indoor and outdoor scenes with different photometric and geometric transformations and our experiments support our claim to being robust against these.
Keyphrases
efficient dense descriptor wide baseline stereo geometric transformation wide-baseline image pair wide-baseline situation dense depth local image descriptor outdoor scene different photometric many experiment matching performance depth estimation accuracy dense depth map occlusion map em-based algorithm first algorithm good one narrowbaseline stereo laser-scanned ground truth scene occlusion detection correlation-based algorithm
