Guided-MLESAC: faster image transform estimation by using matching priors.
MLESAC is an established algorithm for maximum-likelihood estimation by random sampling consensus, devised for computing multiview entities like the fundamental matrix from correspondences between image features. A shortcoming of the method is that it assumes that little is known about the prior pro...
Auteurs principaux: | Tordoff, B, Murray, D |
---|---|
Format: | Journal article |
Langue: | English |
Publié: |
2005
|
Documents similaires
-
MLESAC: a new robust estimator with application to estimating image geometry
par: Torr, PHS, et autres
Publié: (2000) -
Guided sampling and consensus for motion estimation
par: Tordoff, B, et autres
Publié: (2002) -
Faster and Simpler Approximation of Stable Matchings
par: Katarzyna Paluch
Publié: (2014-04-01) -
Image matching via progressive priors
par: Weiqing Wang, et autres
Publié: (2022-09-01) -
Faster Deterministic Distributed MIS and Approximate Matching
par: Ghaffari, Mohsen, et autres
Publié: (2023)