Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/104485
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Efficient guided hypothesis generation for multi-structure epipolar geometry estimation |
Author: | Lai, T. Wang, H. Yan, Y. Xiao, G. Suter, D. |
Citation: | Computer Vision and Image Understanding, 2017; 154:152-165 |
Publisher: | Elsevier |
Issue Date: | 2017 |
ISSN: | 1077-3142 1090-235X |
Statement of Responsibility: | Taotao Lai, Hanzi Wang, Yan Yan , Guobao Xiao, David Suter |
Abstract: | Abstract not available |
Keywords: | Epipolar geometry estimation; multiple structures; guided sampling; joint feature distributions |
Rights: | © 2016 Elsevier Inc. All rights reserved. |
DOI: | 10.1016/j.cviu.2016.10.003 |
Grant ID: | http://purl.org/au-research/grants/arc/DP130102524 |
Published version: | http://dx.doi.org/10.1016/j.cviu.2016.10.003 |
Appears in Collections: | Aurora harvest 3 Computer Science publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.