Automatic Camera Calibration and Model Reconstruction Using Multi-View Stereo
Date Issued
2009
Date
2009
Author(s)
Lin, Liang-Chun
Abstract
In this paper, we propose a method for automatic camera calibration and model reconstruction from image sequences. Our approach for camera calibration consists of two steps. The first step is based on the recent work of structure from motion that recovers camera orientations and positions from a sets of corresponding features points extracted from images. The second step exploits the concept of silhouette coherence to refine camera parameters in the way that the projections of the reconstructed visual hull can be consistent with the original silhouettes as much as possible. Once camera parameters have been recovered, our multi-view stereo reconstruction use a graph-cuts algorithm to carved the visual hull by optimizing the photo-consistency of the surface in a global manner to pursue concavities. A set of surface points identified from silhouettes are also imposed to the optimization as hard constraints to preserve protrusions of the surface.he proposed method is shown to perform well on camera calibration for real data, and the results of model reconstruction are also satisfactory. Since it does not require images being calibrated in advance, our work is suitable for applying augmented reality on the museum exhibition and the digital archives of museum artifacts.
Subjects
Multi-View Stereo
Structure from Motion
Visual Hull
Volumetric Graph-Cuts
Silhouette Coherence
Photo-Consistency
Type
thesis
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