DeReEs: real-time registration of RGBD images using image-based feature detection and robust 3D correspondence estimation and refinement

Seifi, Sahand (2014) DeReEs: real-time registration of RGBD images using image-based feature detection and robust 3D correspondence estimation and refinement. Masters thesis, Memorial University of Newfoundland.

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Abstract

We present DeReEs, a real-time RGBD registration algorithm for the scenario where multiple RGBD images of the same scene are obtained from depth-sensing cameras placed at different viewpoints, with partial overlaps between their views. DeReEs (Detection, Rejection and Estimation) is a combination of 2D image-based feature detection algorithms, a RANSAC based false correspondence rejection and a rigid 3D transformation estimation. DeReEs performs global registration not only in real-time, but also supports large transformation distances for both translations and rotations. DeReEs is designed as part of a virtual/augmented reality solution for a remote 3D collaboration system that does not require initial setup and allows users to freely move the cameras during use. We present comparisons of DeReEs with other common registration algorithms. Our results suggest that DeReEs provides better speed and accuracy especially in scenes with partial overlapping.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/8462
Item ID: 8462
Additional Information: Includes bibliographical references (pages 104-115).
Keywords: alignment, registration, multi-camera, feature-based registration, reconstruction, 3d
Department(s): Science, Faculty of > Computer Science
Date: September 2014
Date Type: Submission
Library of Congress Subject Heading: Computer vision; Image registration; Image processing--Digital techniques

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