Virtual flood experience systems, which enable users to vividly experience flooding, are attracting increasing attention as effective tools for communicating flood risks. However, existing systems typically rely on virtual cities that do not correspond to real locations and often lack sufficient photorealism, limiting users’ ability to relate scenarios to their own surroundings. Although 360° video-based virtual environments offer a simple and scalable way to visually replicate real-world scenes, effective 3D flood visualization in these environments typically requires 3D building geometry of the target area, which is not readily available in many regions. To address this limitation, we propose a new virtual flood experience framework that integrates 360° videos with 3D models automatically constructed from widely available 2D building footprints. By extruding footprints to plausible heights and spatially aligning the constructed models with 360° videos, our framework enables 3D flood visualization in photorealistic environments without relying on pre-existing city models such as CityGML. We demonstrate the framework in Memuro, Hokkaido, Japan, an area vulnerable to river flooding. A user study with local residents showed that the proposed system enhances users’ ability to envision location-specific flood evacuation situations, demonstrating its potential as an effective tool for disaster risk communication and education.

We introduce a novel urban visualization system that integrates 3D urban model (CityGML) and 360$^{\circ }$∘ walkthrough videos. By aligning the videos with the model and dynamically projecting relevant video frames onto the geometries, our system creates photorealistic urban visualizations, allowing users to intuitively interpret geospatial data from a pedestrian view.

We propose a system to generate 360° realistic virtual worlds (360RVW) for the interactive spatial exploration of omnidirectional street-view videos. Our 360RVW enables users to explore photorealistic scenes with digital avatars, and interact with others. To create the virtual worlds our system only requires 360° videos with annotations of the start and end camera coordinate as input. We first detect street intersections to divide the input videos and remove the camera operator from the recordings using a video completion technique. Next, we analyze the 3D structure of the scene using semantic segmentation to define walkable areas. Finally, we render the environment using an ellipsoid projection surface to achieve a more realistic integration of the avatar into real-world 360° videos. The whole process is largely automated, enabling users to produce realistic and interactive virtual worlds without specialized skills or time-consuming manual interventions.