Multiview Stereo via Volumetric Graph-Cuts and Occlusion Robust Photo-Consistency
IEEE Transactions on Pattern Analysis and Machine Intelligence
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SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
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SCIA'07 Proceedings of the 15th Scandinavian conference on Image analysis
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ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
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Editor's Choice Article: Video-based, real-time multi-view stereo
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Scene reconstruction and visualization from internet photo collections
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ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
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MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Image and Vision Computing
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International Journal of Computer Vision
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ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
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International Journal of Computational Science and Engineering
Technical Section: High-resolution depth for binocular image-based modeling
Computers and Graphics
Incremental 3D reconstruction using Bayesian learning
Applied Intelligence
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We present an extremely simple yet robust multi-view stereo algorithm and analyze its properties. The algorithm first computes individual depth maps using a window-based voting approach that returns only good matches. The depth maps are then merged into a single mesh using a straightforward volumetric approach. We show results for several datasets, showing accuracy comparable to the best of the current state of the art techniques and rivaling more complex algorithms.