A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos
ETH Zurich · Institute of Geodesy and Cartography · +2 more institutions
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 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…
Citation impact
- FWCI
- 19.50
- Percentile
- 100%
- References
- 54
Authors
7Topics & keywords
- Computer science
- Benchmark (surveying)
- Computer vision
- Artificial intelligence
- Ranging
- Image resolution
- Set (abstract data type)
- Stereo imaging