Indoor camera pose estimation via style‐transfer 3D models

Abstract

AbstractMany vision‐based indoor localization methods require tedious and comprehensive pre‐mapping of built environments. This research proposes a mapping‐free approach to estimating indoor camera poses based on a 3D style‐transferred building information model (BIM) and photogrammetry technique. To address the cross‐domain gap between virtual 3D models and real‐life photographs, a CycleGAN model was developed to transform BIM renderings into photorealistic images. A photogrammetry‐based algorithm was developed to estimate camera pose using the visual and spatial information extracted from the style‐transferred BIM. The experiments demonstrated the efficacy of CycleGAN in bridging the cross‐domain gap, which significantly improved performance in terms of image retrieval and feature correspondence detection. With the 3D coordinates retrieved from BIM, the proposed method can achieve near real‐time camera pose estimation with an accuracy of 1.38 m and 10.1° in indoor environments.