Robust variational reconstruction from multiple views

Authors:
Natalia Slesareva;Thomas Bühler;Kai Uwe Hagenburg;Joachim Weickert;Andrés Bruhn;Zachi Karni;Hans-Peter Seidel
Affiliations:
Mathematical Image Analysis Group, Dept. of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Mathematical Image Analysis Group, Dept. of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Mathematical Image Analysis Group, Dept. of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Mathematical Image Analysis Group, Dept. of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Mathematical Image Analysis Group, Dept. of Mathematics and Computer Science, Saarland University, Saarbrücken, Germany;Max-Planck-Institut für Informatik, Saarbrücken, Germany;Max-Planck-Institut für Informatik, Saarbrücken, Germany
Venue:
SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
Year:
2007

Citing 10
Cited 0

An Investigation of Smoothness Constraints for the Estimation of Displacement Vector Fields from Image Sequences

IEEE Transactions on Pattern Analysis and Machine Intelligence
Tracking with reference images: a real-time and markerless tracking solution for out-door augmented reality applications

Proceedings of the 2001 conference on Virtual reality, archeology, and cultural heritage
Model-Free Augmented Reality by Virtual Visual Servoing

ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Modelling Dynamic Scenes by Registering Multi-View Image Sequences

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
A Multigrid Platform for Real-Time Motion Computation with Discontinuity-Preserving Variational Methods

International Journal of Computer Vision
Structure from motion for scenes without features

CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Variational shape and reflectance estimation under changing light and viewpoints

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Carved visual hulls for image-based modeling

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Differential geometric consistency extends stereo to curved surfaces

ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Variational principles, surface evolution, PDEs, level set methods, and the stereo problem

IEEE Transactions on Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Recovering a 3-D scene from multiple 2-D views is indispensable for many computer vision applications ranging from free viewpoint video to face recognition. Ideally the recovered depth map should be dense, piecewise smooth with fine level of details, and the recovery procedure shall be robust with respect to outliers and global illumination changes. We present a novel variational approach that satisfies these needs. Our model incorporates robust penalisation in the data term and anisotropic regularisation in the smoothness term. In order to render the data term robust with respect to global illumination changes, a gradient constancy assumption is applied to logarithmically transformed input data. Focussing on translational camera motion and considering small baseline distances between the different camera positions, we reconstruct a common disparity map that allows to track image points throughout the entire sequence. Experiments on synthetic image data demonstrate the favourable performance of our novel method.