We present a new multi-sensor dataset for multi-view 3D surface reconstruction. It includes registered RGB and depth data from sensors of different resolutions and modalities: smartphones, Intel RealSense, Microsoft Kinect, industrial cameras, and structured-light scanner. The data for each scene is obtained under a large number of lighting conditions, and the scenes are selected to emphasize a diverse set of material properties challenging for existing algorithms. Overall, we provide around 1.4 million images of 107 different scenes acquired at 14 lighting conditions from 100 viewing directions. We expect our dataset will be useful for evaluation and training of 3D reconstruction algorithms of different types and for other related tasks.
翻译:我们为多视3D表面重建提供了一套新的多传感器数据集,其中包括注册的RGB和来自不同分辨率和模式传感器的深度数据:智能手机、英特尔RealSense、微软Kinect、工业照相机和结构光扫描仪,每个场景的数据都是在大量照明条件下获得的,选择场景是为了强调对现行算法具有挑战性的各种物质特性。总体而言,我们提供了大约140万张图像,其中107个场景以14个照明条件从100个查看方向获得。我们期望我们的数据集将有助于评估和培训不同类型3D重建算法和其他相关任务。