Hierarchical Shape Description of Objects by Selection and Modification of Prototypes
Hierarchical Shape Description of Objects by Selection and Modification of Prototypes
Blocks world revisited: image understanding using qualitative geometry and mechanics
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Inference and Learning with Hierarchical Shape Models
International Journal of Computer Vision
Degen generalized cylinders and their properties
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Intrinsic characteristics as the interface between CAD and machine vision systems
Pattern Recognition Letters
A Computational Learning Theory of Active Object Recognition Under Uncertainty
International Journal of Computer Vision
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ACRONYM Is a model-based image understanding system. It demonstrates mechanisms for interpretation of images with generic object classes and generic viewing conditions, in a way that is generalizable. It incorporates a powerful geometric modeling capability with a high level modeling language for natural communication with the user In terms of object models. A user gives high level descriptions of both generic and specific instances of objects. A rule-based Inference system produces a viewpoint dependent symbolic summary of the predicted appearance of the objects. This geometric reasoning capability enables the system to incorporate and relate knowledge and information at different levels. This summary drives a powerful syntactic matcher to find instances of the objects in preprocessed images.