Authors:
Daniel Barath
and
Ivan Eichhardt
Affiliation:
MTA SZTAKI and Eötvös Loránd University, Hungary
Keyword(s):
Surface Normal Estimation, Affine Transformation, Stereo Reconstruction, Oriented Point Cloud, Planar Patch.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Geometry and Modeling
;
Image-Based Modeling
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Software Engineering
;
Stereo Vision and Structure from Motion
Abstract:
Nowadays multi-view stereo reconstruction algorithms can achieve impressive results using many views of the scene. Our primary objective is to robustly extract more information about the underlying surface from fewer images. We present a method for point-wise surface normal and tangent plane estimation in stereo case to reconstruct real-world scenes. The proposed algorithm works for general camera model, however, we choose the pinhole-camera in order to demonstrate its efficiency. The presented method uses particle swarm optimization under geometric and epipolar constraints in order to achieve suitable speed and quality. An oriented point cloud is generated using a single point correspondence for each oriented 3D point and a cost function based on photo-consistency. It can straightforwardly be extended to multi-view reconstruction. Our method is validated in both synthesized and real tests. The proposed algorithm is compared to one of the state-of-the-art patch-based multi-view recon
struction algorithms.
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