Automated creation of image-based virtual reality

While virtual reality is a powerful tool for a range of applications, it has the following two associated overheads that fundamentally limit its usefulness: (1) The creation of realistic synthetic virtual environment models is difficult and labor intensive; (2) The computing resources needed to render realistic complex environments in real time are substantial. In this paper, we describe an approach to the fully automated creation of image based virtual reality (VR) models: collections of panoramic images (cylindrical or spherical images) that illustrate an environment. Traditionally, a key bottleneck for this kind of modeling is the selection and acquisition of sample data. Our approach is based on using a small mobile robot to navigate in the environment and collect the image data of interest. A critical issue is selecting the appropriate sample locations of the modeling process: this is addressed using a computational mechanism that resembles human attention. Our objective is to select regions that differ from the surrounding environment. We do this using statistical properties of the output of an edge operator. Specifically, we guide a camera-carrying mobile robot through an environment and have it acquire data with which we construct a VR model. We then demonstrate the effectiveness of our approach using real data.