Perceptual organization and the representation of natural form
Artificial Intelligence
Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic extraction of deformable part models
International Journal of Computer Vision
Recognition of generic components using logic-program relations of image contours
Image and Vision Computing
Recognizing solid objects by alignment with an image
International Journal of Computer Vision
Dynamic 3D Models with Local and Global Deformations: Deformable Superquadrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Invariant Descriptors for 3D Object Recognition and Pose
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
3-D Shape Recovery Using Distributed Aspect Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part II
Part decomposition of objects from single view line drawings
CVGIP: Image Understanding
From volumes to views: an approach to 3-D object recognition
CVGIP: Image Understanding - Special issue on directions in CAD-based vision
Recognizing geons from superquadratics fitted to range data
Image and Vision Computing - Special issue: range image understanding
A direct recovery of superquadric models in range images using recover-and-select paradigm
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Visual learning and recognition of 3-D objects from appearance
International Journal of Computer Vision
The Role of Model-Based Segmentation in the Recovery of Volumetric Parts From Range Data
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIAM Journal on Computing
Shock Graphs and Shape Matching
International Journal of Computer Vision
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Darboux Frames, Snakes, and Super-Quadrics: Geometry from the Bottom Up
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Learning of Models for Recognition
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Combining greyvalue invariants with local constraints for object recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Dealing with occlusions in the eigenspace approach
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Image Segmentation Using Local Variation
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Hierarchical Organization of Appearance-Based Parts and Relations for Object Recognition
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts
Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts
A Cubist Approach to Object Recognition
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Computer Description of Curved Objects
IEEE Transactions on Computers
Journal of Cognitive Neuroscience
A hierarchical concept oriented representation for spatial cognition in mobile robots
50 years of artificial intelligence
Coarse-to-Fine object recognition using shock graphs
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
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The recognition community has long avoided bridging the representational gap between traditional, low-level image features and generic models. Instead, the gap has been eliminated by either bringing the image closer to the models, using simple scenes containing idealized, textureless objects, or by bringing the models closer to the images, using 3-D CAD model templates or 2-D appearance model templates. In this paper, we attempt to bridge the representational gap for the domain of model acquisition. Specifically, we address the problem of automatically acquiring a generic 2-D view-based class model from a set of images, each containing an exemplar object belonging to that class. We introduce a novel graph-theoretical formulation of the problem, and demonstrate the approach on real imagery.