Algorithms for clustering data
Algorithms for clustering data
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Representing and Recognizing the Visual Appearance of Materials using Three-dimensional Textons
International Journal of Computer Vision
Creating a panoramic field image using multi-spectral stereovision system
Computers and Electronics in Agriculture
Original paper: A vision based row detection system for sugar beet
Computers and Electronics in Agriculture
Autopilot for a combine harvester
Computers and Electronics in Agriculture
Mapping, navigation, and learning for off-road traversal
Journal of Field Robotics - Special Issue on LAGR Program, Part I
Corn plant sensing using real-time stereo vision
Journal of Field Robotics - Agricultural Robotics
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Research highlights: @? Robust vision using texture analysis for tracking of field structures. @? Fault-tolerant learning using stereo vision and texture. @? Automatic baling obtained using vision and feedback from implement. @? Field tests validated the quality of theoretical results. Abstract: This paper presents advances in automated baling using stereo vision. A robust classification scheme is developed for learning and classifying based on texture and shape. Using a state-of-the-art texton approach a fast classifier is suggested that can handle non-linearities and artifacts in data. Shape information is employed to make the classifier robust to large variations in lighting conditions and greatly reduce the likelihood that artifacts in signals from the stereo vision system lead to gross errors in estimated object positions. The classifier is tested on data from a stereovision guidance system on a tractor. The system is shown to be able to classify cut plant material (called swath) by learning its appearance. A 3D classifier is successfully used to train the texture classifier. It is demonstrated from field tests how fault-tolerant fusion of steering reference data are obtained for an automated baling vehicle.