A Multi-View Stereo Benchmark with
High-Resolution Images and Multi-Camera Videos
Abstract
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 fieldsof-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. We make our datasets and an online evaluation
server available at http://www.eth3d.net