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Recovering Euclidean deformable models from stereo-motion

In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence

漏 19th International Conference on Pattern Recognition : 2008 : ICPR 2008, 2008, p. 1-4

IEEE

Author: Llad贸 Bardera, Xavier
Del Bue, Alessio
Agapito, Lourdes
Date: 2008
Abstract: In this paper we present a novel structure from motion (SfM) approach able to infer 3D deformable models from uncalibrated stereo images. Using a stereo setup dramatically improves the 3D model estimation when the observed 3D shape is mostly deforming without undergoing strong rigid motion. Our approach first calibrates the stereo system automatically and then computes a single metric rigid structure for each frame. Afterwards, these 3D shapes are aligned to a reference view using a RANSAC method in order to compute the mean shape of the object and to select the subset of points on the object which have remained rigid throughout the sequence without deforming. The selected rigid points are then used to compute frame-wise shape registration and to extract the motion parameters robustly from frame to frame. Finally, all this information is used in a global optimization stage with bundle adjustment which allows to refine the frame-wise initial solution and also to recover the non-rigid 3D model. We show results on synthetic and real data that prove the performance of the proposed method even when there is no rigid motion in the original sequence
Format: application/pdf
Citation: Llad贸, X., Del Bue, A., i Agapito, L. (2008). Recovering Euclidean deformable models from stereo-motion. 19th International Conference on Pattern Recognition : 2008 : ICPR 2008, 1-4. Recuperat 05 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4761003
ISBN: 978-1-4244-2174-9
ISSN: 1051-4651
Document access: http://hdl.handle.net/10256/2165
Language: eng
Publisher: IEEE
Collection: Reproducci贸 digital del document publicat a: http://dx.doi.org/10.1109/ICPR.2008.4761003
Articles publicats (D-ATC)
Is part of: 漏 19th International Conference on Pattern Recognition : 2008 : ICPR 2008, 2008, p. 1-4
Rights: Tots els drets reservats
Subject: Imatges -- Processament -- T猫cniques digitals
Imatgeria tridimensional
Visualitzaci贸 tridimensional (Inform脿tica)
Image processing -- Digital techniques
Three-dimensional display systems
Three-dimensional imaging
Title: Recovering Euclidean deformable models from stereo-motion
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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