LAUSR

In this paper, we introduce a cost-efficient framework that renders a realistic representation of a physical environment using panoramic videos. The framework includes the following main modules: 1) video capturing and stitching, 2) camera trajectory estimation in the panoramic video using computer vision techniques, and 3) generation of virtual experiences using annotations that are integrated into the panoramic video. To quantify the framework performance in terms of processing time, we conducted experiments in three different large environments using a 3.5GHz desktop computer for processing. We show that the proposed framework processing time is less than a minute per meter of the recorded path in the physical environment which is a significant reduction compared to traditional 3D modeling approaches. While the cost savings are substantial, the framework enables the users to explore the virtual environment only along the recorded paths. The proposed framework provides an opportunity to develop applications (e.g. simulation-based training) with limited budgets and still meet the requirement of a very accurate representation of the physical indoor environment.