Marching cubes: A high resolution 3D surface construction algorithm
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
A volumetric method for building complex models from range images
SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Geometric fusion for a hand-held 3D sensor
Machine Vision and Applications
Automatic 3D Model Construction for Turn-Table Sequences
SMILE'98 Proceedings of the European Workshop on 3D Structure from Multiple Images of Large-Scale Environments
Constructing Virtual Worlds Using Dense Stereo
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Image-based rendering using image-based priors
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Bayesian 3D Modeling from Images Using Multiple Depth Maps
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
ACM SIGGRAPH 2007 papers
Interactive 3D architectural modeling from unordered photo collections
ACM SIGGRAPH Asia 2008 papers
Make3D: Learning 3D Scene Structure from a Single Still Image
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Although the visual perception of 3D shape from 2D images is a basic capability of human beings, it remains challenging to computers Hence, one goal of vision research is to computationally understand and model the latent 3D scene from the captured images, and provide human-like visual system for machines In this paper, we present a method that is capable of building a realistic 3D model for the latent scene from multiple images taken at different viewpoints Specifically, the reconstruction proceeds in two steps First, generate dense depth map for each input image by a Bayesian-based inference model Second, build a complete 3D model for the latent scene by integrating all reliable 3D information embedded in the depth maps Experiments are conducted to demonstrate the effectiveness of the proposed approach.