Towards a Calibrated 360° Stereoscopic HDR Image Dataset for Architectural Lighting Studies

Abstract

High fidelity 360 • images enhance user experience and offer realistic representations for architectural design studies. Specifically, VR and hyper-realistic imaging technologies can be helpful tools to study daylight in architectural places thanks to the high level of immersion and its ability to create perceptually accurate and faithful scene representations. In this paper, we present a novel method for collecting and processing physically calibrated 360 • stereoscopic high-dynamic range images of daylit indoor places. The future dataset aims to provide a higher degree of realism, a wide range of various luminous interior spaces supplied with information on the physical characterization of the space. This paper presents the first applications of this method on different places and discusses challenges for assessing visual perception in these images. In the near future, this dataset will be publicly available for architectural as well as multimedia studies. Keywords image dataset • high dynamic range • omnidirectional • light studies • architecture • visual perception • virtual reality