Stochastic sampling in computer graphics
ACM Transactions on Graphics (TOG)
The MPEG-4 Multimedia Coding Standard: Algorithms, Architectures and Applications
Journal of VLSI Signal Processing Systems - Special issue on implementation of MPEG-4 multimedia codecs
Geometric Camera Calibration Using Circular Control Points
IEEE Transactions on Pattern Analysis and Machine Intelligence
A compact algorithm for rectification of stereo pairs
Machine Vision and Applications
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Shape by Space Carving
International Journal of Computer Vision - Special issue on Genomic Signal Processing
Comparing Images Using the Hausdorff Distance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reconstructing Surfaces by Volumetric Regularization Using Radial Basis Functions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Gradient Vector Flow: A New External Force for Snakes
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Benchmarking Least Squares Support Vector Machine Classifiers
Machine Learning
Methods for Volumetric Reconstruction of Visual Scenes
International Journal of Computer Vision
Silhouette and stereo fusion for 3D object modeling
Computer Vision and Image Understanding - Model-based and image-based 3D scene representation for interactive visalization
Multi-View Stereo Reconstruction of Dense Shape and Complex Appearance
International Journal of Computer 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
Appearance-Cloning: Photo-Consistent Scene Recovery from Multi-View Images
International Journal of Computer Vision
Accurate and Scalable Surface Representation and Reconstruction from Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel-based classification using quantum mechanics
Pattern Recognition
International Journal of Computer Vision
Robust Recovery of Shapes with Unknown Topology from the Dual Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A semi-supervised approach to space carving
Pattern Recognition
Kernel bandwidth estimation for nonparametric modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Boosting support vector machines for imbalanced data sets
Knowledge and Information Systems
Carved visual hulls for image-based modeling
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Comparing support vector machines with Gaussian kernels to radialbasis function classifiers
IEEE Transactions on Signal Processing
The estimation of the gradient of a density function, with applications in pattern recognition
IEEE Transactions on Information Theory
Variational principles, surface evolution, PDEs, level set methods, and the stereo problem
IEEE Transactions on Image Processing
Object classification in 3-D images using alpha-trimmed mean radial basis function network
IEEE Transactions on Image Processing
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This paper proposes a new approach for multi-object 3D scene modeling. Scenes with multiple objects are characterized by object occlusions under several views, complex illumination conditions due to multiple reflections and shadows, as well as a variety of object shapes and surface properties. These factors raise huge challenges when attempting to model real 3D multi-object scene by using existing approaches which are designed mainly for single object modeling. The proposed method relies on the initialization provided by a rough 3D model of the scene estimated from the given set of multi-view images. The contributions described in this paper consists of two new methods for identifying and correcting errors in the reconstructed 3D scene. The first approach corrects the location of 3D patches from the scene after detecting the disparity between pairs of their projections into images. The second approach is called shape-from-contours and identifies discrepancies between projections of 3D objects and their corresponding contours, segmented from images. Both unsupervised and supervised segmentations are used to define the contours of objects.