Location and 3-D Visual Awareness-Based Dynamic Texture Updating for Indoor 3-D Model

3-D visualization of location-based services (LBSs) in a geographic information system (GIS) and the Internet-of-Things (IoT) applications could enhance the user experience. Texture is generally the most noticeable visual element in a 3-D indoor model. However, it usually tends to be outdated and becomes inaccurate in complex and dynamic environments. The applications of such 3-D visualizations, especially in indoor environments, are further impeded by a limited capacity to represent frequently changing scenes due to object displacements. To overcome this problem, a novel location and 3-D visual awareness-based method is proposed to automatically register and update a live image onto a 3-D indoor model. In this method, a multisensor fusion-based indoor localization algorithm employs an indoor map to integrate multisource data, including activity detection information, pedestrian dead reckoning (PDR), and 3-D vision-based localization data. Based on the positioning results, we locate the region of the photograph capture within a scene and identify the triangular meshes of the facing wall. The texture is extracted from real-time images through a 3-D indoor understanding technique and automatically fused with the indoor 3-D model. The geometric relationship between texture and the 3-D indoor model is established by calculating the UV coordinates. The experimental results demonstrate that our approach can accurately update the dynamic indoor model textures regardless of the scene. Based on this texture updating technique, users experience an enhanced presentation of LBS information on our 3-D visualization platform.