Registered Relief Depth (RRD) borobudur dataset for single-frame depth prediction on one-side artifacts

Single-frame depth prediction is an efficient 3D reconstruction method for one-side artifacts. However, for this purpose, ground truth images, where the pixels are associated with the actual depth, are needed. The small number of publicly accessible datasets is an issue with the restoration of cultural heritage objects. In addition, relief data with irregular characteristics due to nature and human treatment, such as decolorization caused by moss and chemical reaction is still not available. We therefore created a dataset of Borobudur temple reliefs registered with their depth for data availability to solve these problems. This data collection consists of 4608 x 3456 (4K) resolution and profound RGB frames and we call this dataset the Registered Relief Depth (RRD) Borobudur Dataset. The RGB images have been taken using an Olympus EM10 II Camera with a 14 mm f/3.5 lens and the depth images were obtained directly using an ASUS XTION scanner, acquired on the temple's reliefs at 15000-25000 lux day time. The registration process of RGB data and depth in-formation was manually performed via control points and was directly supervised by the archaeologist. Apart of enrich-ing the data availability, this dataset can become an opportu-nity for International researchers to understand more about Indonesian Cultural Heritages. (C) 2021 The Authors. Published by Elsevier Inc.