Using Spin Images for Efficient Object Recognition in Cluttered 3D Scenes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Detection of Human Nudes
International Journal of Computer Vision - 1998 Marr Prize
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International Journal of Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Shape, Contour and Grouping in Computer Vision
Shape, Contour and Grouping in Computer Vision
A Comparative Study of Polynomial Kernel SVM Applied to Appearance-Based Object Recognition
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
SVM '02 Proceedings of the First International Workshop on Pattern Recognition with Support Vector Machines
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
Flexible Spatial Configuration of Local Image Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Eigendecomposition of images correlated on S1, S2, and SO(3) using spectral theory
IEEE Transactions on Image Processing
Designing eigenspace manifolds: with application to object identification and pose estimation
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
LWDOS: language for writing descriptors of outline shapes
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
ICECS'05 Proceedings of the 4th WSEAS international conference on Electronics, control and signal processing
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The recognition of general three-dimensional objects in cluttered scenes is a challenging problem. In particular, the design of a good representation suitable to model large numbers of generic objects that is also robust to occlusion has been an stumbling block in achieving success. In this paper, we propose a representation using appearance-based parts and relations to overcome these problems. Appearance-based parts and relations are defined in terms of closed regions and the union of these regions, respectively. The regions are segmented using the MDL principle, and their appearance is obtained from collection of images and compactly represented by parametric manifolds in the two eigenspaces spanned by the parts and the relations.