Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/55486
Type: Conference paper
Title: Robust motion estimation and structure recovery from endoscopic image sequences with an adaptive Scale Kernel Consensus estimator
Author: Wang, H.
Mirota, D.
Ishii, M.
Hager, G.
Citation: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2008: pp.1-7
Publisher: IEEE
Publisher Place: Online
Issue Date: 2008
ISBN: 9781424422425
Conference Name: IEEE Conference on Computer Vision and Pattern Recognition (21st : 2008 : Anchorage, AK)
Statement of
Responsibility: 
Hanzi Wang; Mirota, D.; Ishii, M. and Hager, G.D.
Abstract: To correctly estimate the camera motion parameters and reconstruct the structure of the surrounding tissues from endoscopic image sequences, we need not only to deal with outliers (e.g., mismatches), which may involve more than 50% of the data, but also to accurately distinguish inliers (correct matches) from outliers. In this paper, we propose a new robust estimator, Adaptive Scale Kernel Consensus (ASKC), which can tolerate more than 50 percent outliers while automatically estimating the scale of inliers. With ASKC, we develop a reliable feature tracking algorithm. This, in turn, allows us to develop a complete system for estimating endoscopic camera motion and reconstructing anatomical structures from endoscopic image sequences. Preliminary experiments on endoscopic sinus imagery have achieved promising results.
RMID: 0020093978
Description (link): http://dx.doi.org/10.1109/CVPR.2008.4587687
Appears in Collections: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.