Topology matching for fully automatic similarity estimation of 3D shapes
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
ACM Transactions on Graphics (TOG)
A Reflective Symmetry Descriptor
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Matching 3D Models with Shape Distributions
SMI '01 Proceedings of the International Conference on Shape Modeling & Applications
A Reflective Symmetry Descriptor for 3D Models
Algorithmica
Journal of Cognitive Neuroscience
3D model retrieval based on adaptive views clustering
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
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In this paper, we propose new methods for recognizing 2D/3D objects undergoing affine transforms. Robustness with respect to level-of-detail is achieved by selection of points belonging to fixed directions on a circle, i.e., the 2D case, or a sphere, i.e., the 3D case (called the Ray casting selection method in the literature). The proposed descriptors are based on principal component analysis (PCA); each shape is represented by its eigenvalues and the corresponding eigenvectors.The proposed methods allow recognition under an affine transform which is not possible using other methods in the literature, for example, that in [1]. Here we use an asymmetric PCA to achieve invariance under an affine transform.