Name
Abstract | ||
|---|---|---|
This work introduces an original method for registering pairs of 3D views consisting of range data sets which operates in the frequency domain. The Fourier transform allows the decoupling of the estimate of the rotation parameters from the estimate of the translation parameters, our algorithm exploits this well-known property by suggesting a three-step procedure. The rotation parameters are estimated by the first two steps through convenient representations and projections of the Fourier transforms' magnitudes and the translational displacement is recovered by the third step by means of a standard phase correlation technique after compensating one of the two views for rotation. The performance of the algorithm, which is well-suited for unsupervised registration, is clearly assessed through extensive testing with several objects and shows that good and robust estimates of 3D rigid motion are achievable. Our algorithm can be used as a prealignment tool for more accurate space-domain registration techniques, like the ICP algorithm. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/TPAMI.2002.1046160 | IEEE Trans. Pattern Anal. Mach. Intell. |
Keywords | Field | DocType |
frequency domain technique,fourier transforms,convenient representation,algorithm performance,3d rigid motion,robust estimate,fourier transform,parameter estimation,icp algorithm,space-domain registration techniques,frequency-domain analysis,rotation parameter,range data registration,prealignment tool,frequency domain,standard phase correlation technique,extensive testing,image registration,unsupervised registration,accurate space-domain registration technique,translation parameter estimation,original method,3d views,rotation parameter estimation,image motion analysis,robust estimator,testing,frequency domain analysis,solid modeling,phase correlation,image segmentation,motion estimation,robustness | Frequency domain,Computer vision,Data set,Pattern recognition,Computer science,Robustness (computer science),Image segmentation,Fourier transform,Artificial intelligence,Motion estimation,Image registration,Phase correlation | Journal |
Volume | Issue | ISSN |
24 | 11 | 0162-8828 |
Citations | PageRank | References |
51 | 2.66 | 34 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Luca Lucchese | 1 | 184 | 17.53 |
| Gianfranco Doretto | 2 | 1026 | 78.58 |
| G. Cortelazzo | 3 | 335 | 52.48 |