Multiple Resolution Segmentation of Textured Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
A review of recent texture segmentation and feature extraction techniques
CVGIP: Image Understanding
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Bayesian Fusion of Color and Texture Segmentations
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Intelligent Service Robotics
Loop-closing: A typicality approach
Robotics and Autonomous Systems
Efficient roughness recognition for velocity updating by wheeled-robots navigation
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Self-supervised terrain classification for planetary surface exploration rovers
Journal of Field Robotics
Robotics and Autonomous Systems
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Remote sensing of terrain characteristics is an important component for autonomous operation of mobile robots in natural terrain. Often this involves classification of terrain into one of a set of a priori known terrain classes. Situations can frequently arise, however, where an autonomous robot encounters a terrain class that does not belong to one of these known classes. This paper proposes an approach for visual detection of novel terrain based on a two-class support vector machine (SVM) for situations when known terrain classes can be confidently associated with only a subset of the training data. Experimental results from a four-wheeled mobile robot in Mars analog terrain demonstrate the effectiveness of this approach.