Development of Segmentation-Rendering on Virtual Reality for Training Deep-learning, Simulating Landscapes and Advanced User Experience

Abstract

Virtual reality (VR) has been suggested for various purposes in the field of architecture, engineering, and construction (AEC). This research explores new roles for VR toward the super-smart society in the near future. In particular, we propose to develop post-processing rendering, segmentation-rendering and shadow-casting rendering algorithms for novel VR expressions to enable more versatile approaches than the normal photorealistic red, green, and blue (RGB) expressions. We succeeded in applying a wide variety of VR renderings in urban-design projects after implementation. The developed system can create images in real time to train deep-learning algorithms, can also be applied to landscape analysis and contribute to advanced user experience.

Methods for the Prediction and Specification of Functionally Graded Multi-Grain Responsive Timber Composites

“…To solve this challenge, a method has been proposed for automatically generating mask images of buildings, roads, and other objects by using VR 3D models for deep learning (Fukuda et al 2019). By using the 3D virtual model, we can create datasets that include mask images easily and rapidly.…”