Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
A Theory of Shape by Space Carving
International Journal of Computer Vision - Special issue on Genomic Signal Processing
What Energy Functions Can Be Minimized via Graph Cuts?
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Photorealistic Scene Reconstruction by Voxel Coloring
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Tales of Shape and Radiance in Multi-view Stereo
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
An Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Silhouette and stereo fusion for 3D object modeling
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
Globally Optimal Geodesic Active Contours
Journal of Mathematical Imaging and Vision
Multi-View Stereo via Volumetric Graph-Cuts
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Globally Minimal Surfaces by Continuous Maximal Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
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A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Multi-View Stereo Reconstruction and Scene Flow Estimation with a Global Image-Based Matching Score
International Journal of Computer Vision
Multiview Stereo via Volumetric Graph-Cuts and Occlusion Robust Photo-Consistency
IEEE Transactions on Pattern Analysis and Machine Intelligence
Continuous global optimization in multiview 3D reconstruction
EMMCVPR'07 Proceedings of the 6th international conference on Energy minimization methods in computer vision and pattern recognition
Robust variational segmentation of 3d objects from multiple views
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Oriented visibility for multiview reconstruction
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Total variation minimization and a class of binary MRF models
EMMCVPR'05 Proceedings of the 5th international conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
3D surface reconstruction using graph cuts with surface constraints
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Variational principles, surface evolution, PDEs, level set methods, and the stereo problem
IEEE Transactions on Image Processing
Non-parametric Single View Reconstruction of Curved Objects Using Convex Optimization
Proceedings of the 31st DAGM Symposium on Pattern Recognition
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
A convex multi-view stereo formulation with robustness to occlusions and time-varying clutter
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
International Journal of Computer Vision
A local region-based Chan-Vese model for image segmentation
Pattern Recognition
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Proceedings of the 2010 international conference on Video Processing and Computational Video
Multiview visibility estimation for image-based modeling
Journal of Computer Science and Technology - Special issue on Natural Language Processing
Continuous Multiclass Labeling Approaches and Algorithms
SIAM Journal on Imaging Sciences
A Super-Resolution Framework for High-Accuracy Multiview Reconstruction
International Journal of Computer Vision
Total Cyclic Variation and Generalizations
Journal of Mathematical Imaging and Vision
Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
Journal of Mathematical Imaging and Vision
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In this article, we introduce a new global optimization method to the field of multiview 3D reconstruction. While global minimization has been proposed in a discrete formulation in form of the maxflow-mincut framework, we suggest the use of a continuous convex relaxation scheme. Specifically, we propose to cast the problem of 3D shape reconstruction as one of minimizing a spatially continuous convex functional. In qualitative and quantitative evaluation we demonstrate several advantages of the proposed continuous formulation over the discrete graph cut solution. Firstly, geometric properties such as weighted boundary length and surface area are represented in a numerically consistent manner: The continuous convex relaxation assures that the algorithm does not suffer from metrication errors in the sense that the reconstruction converges to the continuous solution as the spatial resolution is increased. Moreover, memory requirements are reduced, allowing for globally optimal reconstructions at higher resolutions.We study three different energy models for multiview reconstruction, which are based on a common variational template unifying regional volumetric terms and on-surface photoconsistency. The three models use data measurements at increasing levels of sophistication. While the first two approaches are based on a classical silhouette-based volume subdivision, the third one relies on stereo information to define regional costs. Furthermore, this scheme is exploited to compute a precise photoconsistency measure as opposed to the classical estimation. All three models are compared on standard data sets demonstrating their advantages and shortcomings. For the third one, which gives the most accurate results, a more exhaustive qualitative and quantitative evaluation is presented.