3D Indoor Virtual Environment Modeling via Vehicle Navigation and Multi-Camera Image Data Fusion

Abstract

In applications of virtual reality, it is often required to establish environment models, which is usually time-consuming. In this study, an offline automatic approach to 3-D indoor virtual environment modeling by the way of autonomous land vehicle (ALV) navigation is proposed. An ALV is first driven manually along a path by a driver to collect environment data using three cameras mounted on the ALV. The system then generates the environment model by a data fusion approach using the model learning result from the multiple-view data, performs intelligent post-processing works to create a more complete model, and uses the VRML language to construct a corresponding 3-D virtual reality (VR) model automatically. Good experimental results prove the feasibility of the proposed approach.