A Multi-View Stereo Benchmark With High-Resolution Images And Multi-Camera Videos

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017)(2017)

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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.
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关键词
multiview stereo benchmark,high-resolution images,multicamera videos,indoor scenes,outdoor scenes,high-precision laser scanner,high-resolution DSLR imagery,synchronized low-resolution stereo videos,fields-of-view,scene types,higher temporal resolution,spatial resolution,high-resolution DSLR camera images,laser scans,geometry,man-made indoor environments,online evaluation server
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