Many 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.

中文翻译：

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通过风格转移 3D 模型进行室内相机姿态估计

许多基于视觉的室内定位方法需要对建筑环境进行繁琐而全面的预映射。本研究提出了一种基于 3D 风格转移建筑信息模型 (BIM) 和摄影测量技术的无映射方法来估计室内摄像机位姿。为了解决虚拟 3D 模型和真实照片之间的跨域差距，开发了 CycleGAN 模型以将 BIM 渲染转换为逼真的图像。开发了一种基于摄影测量的算法，使用从风格转移的 BIM 中提取的视觉和空间信息来估计相机位姿。实验证明了 CycleGAN 在弥合跨域差距方面的功效，显着提高了图像检索和特征对应检测方面的性能。使用从 BIM 检索到的 3D 坐标，