Abstract
A clustering and quadratic programming based projection onto convex sets (CQPOCS) algorithm for fast feature point matching is presented in this paper. Via feature point clustering, the problem of matching model point set and taget point set is converted in to the problem of matching corresponding clusters, thus reducing the computational cost. Then, quadratic programming based POCS algorithm is used to solve the cluster matching problem without incurring the successive POCS algorithm's accumulating deviation due to successive projections onto row convex sets and column convex sets. Simulation results show that our CQPOCS algorithm has satisfactory matching accuracy and computational safety.
Original language | English |
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Pages (from-to) | 240-247 |
Number of pages | 8 |
Journal | Zidonghua Xuebao/Acta Automatica Sinica |
Volume | 33 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2007 |
Keywords
- Clustering
- POCS
- Point matching