Video2Game: Real-time, Interactive, Realistic and Browser-Compatible Environment from a Single Video (2404.09833v1)

Abstract: Creating high-quality and interactive virtual environments, such as games and simulators, often involves complex and costly manual modeling processes. In this paper, we present Video2Game, a novel approach that automatically converts videos of real-world scenes into realistic and interactive game environments. At the heart of our system are three core components:(i) a neural radiance fields (NeRF) module that effectively captures the geometry and visual appearance of the scene; (ii) a mesh module that distills the knowledge from NeRF for faster rendering; and (iii) a physics module that models the interactions and physical dynamics among the objects. By following the carefully designed pipeline, one can construct an interactable and actionable digital replica of the real world. We benchmark our system on both indoor and large-scale outdoor scenes. We show that we can not only produce highly-realistic renderings in real-time, but also build interactive games on top.

• The paper introduces Video2Game, which automatically converts single videos into interactive, photo-realistic 3D environments by integrating neural radiance fields, mesh conversion, and a physics module.
• The methodology leverages advanced NeRF modeling enhanced with depth cues, semantic understanding, and normal prediction to capture detailed geometry and high-fidelity visuals.
• The framework supports real-time, browser-compatible interactions, drastically reducing development time and cost for game prototyping and virtual simulations.

Transforming Videos into Interactive Game Environments with Video2Game

Introduction

The development of virtual environments for use in video games, VR applications, and simulators is a complex and often costly process. It requires a multidisciplinary effort involving artists, programmers, and engineers to create realistic, interactive 3D spaces. The paper introduces Video2Game, a novel framework that leverages videos of real-world scenes to automatically generate interactive and realistic game environments. The core of Video2Game combines neural radiance fields (NeRF) for high-fidelity visual modeling, with a physics module for realistic interactions, and meshes for efficient rendering. These components are integrated into a WebGL-based game engine allowing for real-time user interaction within browser-compatible virtual worlds.

Core Components

• Neural Radiance Fields (NeRF): Video2Game utilizes an advanced NeRF model that captures detailed geometry and visual appearance of the scene. These models have shown promise in rendering photo-realistic static scenes from sparse image data. The paper extends these capabilities to capture large-scale scenes, augmenting traditional NeRF approaches with depth cues, semantic understanding, and normal vector prediction to improve the realism and detail of generated environments.
• Mesh Module: NeRF's high-quality rendering comes at a computational cost, inhibiting real-time interaction. The authors address this by converting the NeRF-generated representations into meshes with neural textures. This allows for significantly faster rendering that retains visual fidelity and supports integration with gaming engines.
• Physics Module: To enrich the interactive experience beyond mere visual exploration, Video2Game incorporates a physics module. This module enables realistic simulations of physical dynamics and interactions within the virtual environment, such as collisions and object manipulation.

Benchmarking and Results

The system was tested on various scene complexities, including both indoor and outdoor environments. The results indicate that Video2Game can produce highly realistic renderings at interactive frame rates. Moreover, the framework demonstrated its capability to allow real-time interactions within these virtual spaces, fulfilling the promise of transforming simple video footage into rich, explorable, and interactive domains.

Implications and Future Directions

The introduction of Video2Game signifies an important advancement in the automation of virtual environment creation. For researchers, game developers, and content creators, the implications are far-reaching. This approach can drastically reduce the time and resources required to produce interactive 3D environments. It opens new possibilities for the rapid prototyping of game levels, simulation scenarios, and virtual experiences directly from real-world footage.

Looking forward, the integration of more complex physical interactions and the enhancement of semantic scene understanding represent promising areas for further development. Additionally, exploring the potential for dynamic scene changes and interactions in real-time within these virtual environments could further bridge the gap between virtual and physical worlds.

Conclusion

Video2Game presents an innovative approach to 3D content creation, leveraging the vast availability of video data to automatically generate interactive, realistic virtual environments. This work marks a significant step forward in the field of generative AI and virtual environment creation, offering a glimpse into the future of interactive media where the lines between the real and the virtual continue to blur. As the technology matures, it has the potential to democratize content creation, making sophisticated virtual experiences accessible to a wider range of creators and audiences alike.