IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Graduated Assignment Algorithm for Graph Matching
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer Vision and Image Understanding
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
Recognition of Shapes by Editing Their Shock Graphs
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using the Inner-Distance for Classification of Articulated Shapes
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Describing and matching 2d shapes by their points of mutual symmetry
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part III
Robust contour matching via the order-preserving assignment problem
IEEE Transactions on Image Processing
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Nowadays in modern medicine, computer modeling has already become one of key methods toward the discovery of new pharmaceuticals. And virtual screening is a necessary process for this discovery. In the procedure of virtual screening, shape matching is the first step to select ligands for binding protein. In the era of HTS (high throughput screening), a fast algorithm with good result is in demand. Many methods have been discovered to fulfill the requirement. Our method, called ''Circular Cone'', by finding principal axis, gives another way toward this problem. We use modified PCA (principal component analysis) to get the principal axis, around which the rotation is like whirling a cone. By using this method, the speed of giving score to a pocket and a ligand is very fast, while the accuracy is ordinary. So, the good speed and the general accuracy of our method present a good choice for HTS.