Authors:
Hyojin Kim
1
;
Quinn Hunter
1
;
Mark Duchaineau
2
;
Kenneth Joy
1
and
Nelson Max
1
Affiliations:
1
University of California, United States
;
2
Lawrence Livermore National Laboratory, United States
Keyword(s):
Multi-view Stereo, 3D Reconstruction, Planar Reconstruction, GPGPU.
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:
This paper presents a new multi-view stereo approach that reconstructs aerial or outdoor scenes in both a planar and a point representation. One of the key features is to integrate two heterogeneous schemes for planar and non-planar reconstruction, given a color segmentation where each segment is classified as either planar or non-planar. In planar reconstruction, an optimal plane for each segment is chosen among possible plane candidates by comparing the remapped reference segment region with multiple target images in parallel on a GPU. In point reconstruction for non-planar objects, remapped pixel descriptors along an epipolar line pair are efficiently matched on a GPU. Our method also detects and discards incorrect segment planes and outliers that have a large 3D discontinuity with the neighboring segment planes. Several aerial and outdoor scene reconstruction results with quantitative analyses are provided.