Abstract
In this paper we consider the problem of automatically determining whether regions in an outdoor environment can be traversed by a mobile robot. We propose a two-level classifier that uses data from a single color image to make this determination. At the low level, we have implemented three classifiers based on color histograms, directional filters and local binary patterns. The outputs of these low level classifiers are combined using a voting scheme that weights the results of each classifier using an estimate of its error probability. We present results from a large number of trials using a database of representative images acquired in real outdoor environments.
| Original language | English (US) |
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| Pages | 297-304 |
| Number of pages | 8 |
| State | Published - 2003 |
| Event | 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems - Las Vegas, NV, United States Duration: Oct 27 2003 → Oct 31 2003 |
Other
| Other | 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems |
|---|---|
| Country/Territory | United States |
| City | Las Vegas, NV |
| Period | 10/27/03 → 10/31/03 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications