A Multi-View Stereo Benchmark with High-Resolution Images and Multi-Camera Videos

被引:396
|
作者
Schops, Thomas [1 ]
Schonberger, Johannes L. [1 ]
Galliani, Silvano [2 ]
Sattler, Torsten [1 ]
Schindler, Konrad [2 ]
Pollefeys, Marc [1 ,4 ]
Geiger, Andreas [1 ,3 ]
机构
[1] Swiss Fed Inst Technol, Dept Comp Sci, Zurich, Switzerland
[2] Swiss Fed Inst Technol, Inst Geodesy & Photogrammetry, Zurich, Switzerland
[3] MPI Intelligent Syst, Autonomous Vis Grp, Tubingen, Germany
[4] Microsoft, Redmond, WA USA
关键词
D O I
10.1109/CVPR.2017.272
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Motivated by the limitations of existing multi-view stereo benchmarks, we present a novel dataset for this task. Towards this goal, we recorded a variety of indoor and outdoor scenes using a high-precision laser scanner and captured both high-resolution DSLR imagery as well as synchronized low-resolution stereo videos with varying fields-of-view. To align the images with the laser scans, we propose a robust technique which minimizes photometric errors conditioned on the geometry. In contrast to previous datasets, our benchmark provides novel challenges and covers a diverse set of viewpoints and scene types, ranging from natural scenes to man-made indoor and outdoor environments. Furthermore, we provide data at significantly higher temporal and spatial resolution. Our benchmark is the first to cover the important use case of hand-held mobile devices while also providing high-resolution DSLR camera images.
引用
收藏
页码:2538 / 2547
页数:10
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