Registration of 3D geometric model and color images using SIFT and range intensity images

  1. Get@NRC: Registration of 3D geometric model and color images using SIFT and range intensity images (Opens in a new window)
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TypeBook Chapter
Proceedings titleAdvances in Visual Computing : 7th International Symposium, ISVC 2011, Las Vegas, NV, USA, September 26-28, 2011. Proceedings, Part I
Series titleLecture Notes In Computer Science; Volume 6938
Conference7th International Symposium on Visual Computing (ISVC 2011), September 26-28, 2011, Las Vegas, Nevada, USA
Pages325336; # of pages: 12
Subject3D geometric model; Background image; Bhattacharyya distance; Color images; Displacement estimation; False matches; Intensity images; Intrinsic parameters; Range images; Range sensors; Real-world objects; Color; Three dimensional
AbstractIn this paper, we propose a new method for 3D-2D registration based on SIFT and a range intensity image, which is a kind of intensity image simultaneously acquired with a range image using an active range sensor. A linear equation for the registration parameters is formulated, which is combined with displacement estimations for extrinsic and intrinsic parameters and the distortion of a camera's lens. This equation is solved to match a range intensity image and a color image using SIFT. The range intensity and color images differ, and the pairs of matched feature points usually contain a number of false matches. To reduce false matches, a range intensity image is combined with the background image of a color image. Then, a range intensity image is corrected for extracting good candidates. Moreover, to remove false matches while keeping correct matches, soft matching, in which false matches are weakly removed, is used. First, false matches are removed by using scale information from SIFT. Secondly, matching reliability is defined from the Bhattacharyya distance of the pair of matched feature points. Then RANSAC is applied. In this stage, its threshold is kept high. In our approach, the accuracy of registration is advanced. The effectiveness of the proposed method is illustrated by experiments with real-world objects. © 2011 Springer-Verlag.
Publication date
PublisherSpringer Berlin Heidelberg
AffiliationNational Research Council Canada (NRC-CNRC)
Peer reviewedYes
NPARC number21271603
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Record identifier9f47ee6d-544b-4ba9-bfdd-4bbc3747113e
Record created2014-03-24
Record modified2016-07-15
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