Model-based strategies for high-level robot vision
Computer Vision, Graphics, and Image Processing
3DPO: A three-dimensional part orientation system
International Journal of Robotics Research
A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detecting buildings in aerial images
Computer Vision, Graphics, and Image Processing
Proceedings of a workshop on Image understanding workshop
Coding and Information Theory
Evaluation of Structure Recognition Using Labelled Facade Images
Proceedings of the 31st DAGM Symposium on Pattern Recognition
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We propose and evaluate a class of objective functions that rank hypotheses for feature labels. Our approach takes into account the representation cost and quality of the shapes themselves, and balances the geometric requirements against the photometric evidence This balance is essential for any system using underconstrained or generic feature models. We introduce examples of specific models allowing the actual computation of the terms in the objective function, and show how this framework leads naturally to control parameters that have a clear semantic meaning. We illustrate the properties of our objective functions on synthetic and real images.