|
While virtual reality is a powerful tool for a range of
applications, it has the following two associated overheads that fundamentally
limit its usefulness:
- The creation of realistic synthetic
virtual environment models is
difficult and labour intensive;
- 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 modelling 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 modelling 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.
|