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...
| Huvudupphovsmän: | , |
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| Materialtyp: | Journal article |
| Språk: | English |
| Publicerad: |
2005
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