Zippered polygon meshes from range images
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Markov random field modeling in computer vision
Markov random field modeling in computer vision
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Registration and Integration of Multiple Object Views for 3D Model Construction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Real-time 3D model acquisition
Proceedings of the 29th 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
The Ball-Pivoting Algorithm for Surface Reconstruction
IEEE Transactions on Visualization and Computer Graphics
What Energy Functions Can Be Minimizedvia Graph Cuts?
IEEE Transactions on Pattern Analysis and Machine Intelligence
Markov random field modeled range image segmentation
Pattern Recognition Letters
Range Image Fusion for Object Reconstruction and Modeling
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
Adaptively Merging Large-Scale Range Data with Reflectance Properties
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Surface modeling using multi-view range and color images
Integrated Computer-Aided Engineering
Accurate integration of multi-view range images using k-means clustering
Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
A clustering approach to free form surface reconstruction from multi-view range images
Image and Vision Computing
Automatic 3d free form shape matching using the graduated assignment algorithm
Pattern Recognition
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Multi-view range image integration focuses on producing a single reasonable 3D point cloud from multiple 2.5D range images for the reconstruction of a watertight manifold surface. However, registration errors and scanning noise usually lead to a poor integration and, as a result, the reconstructed surface cannot have topology and geometry consistent with the data source. This paper proposes a novel method cast in the framework of Markov random fields (MRF) to address the problem. We define a probabilistic description of a MRF labeling based on all input range images and then employ loopy belief propagation to solve this MRF, leading to a globally optimised integration with accurate local details. Experiments show the advantages and superiority of our MRF-based approach over existing methods.