Name
Abstract | ||
|---|---|---|
Both parametric and implicit representations are used in a variety of computer vision applications such as object modeling, recognition and pose estimation. In this paper, we present a new algebraic curve fitting technique based on the implicitization of affine invariant Fourier descriptors that can be used to model free-form objects captured from different viewpoints. Implicitization can be carried out quite efficiently using a numerical procedure rather than computing determinants of eliminant matrices, symbolically. Affine invariance of the proposed fitting technique is experimentally shown on a database of 2D free-form objects. Experimental results are provided to assess the robustness of our fitting method under data perturbations. Some invariant recognition examples are also presented. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/s10044-005-0245-6 | Pattern Anal. Appl. |
Keywords | Field | DocType |
Algebraic curves,Implicit polynomials,Fourier descriptors,Affine invariance,Fitting,Matrix annihilation,Object recognition,Robustness,Implicitization | Affine transformation,Affine shape adaptation,Curve fitting,Algebraic curve,Pose,Artificial intelligence,Affine geometry of curves,Computer vision,Pattern recognition,Algorithm,Parametric statistics,Invariant (mathematics),Mathematics | Journal |
Volume | Issue | ISSN |
8 | 1-2 | 1433-7541 |
Citations | PageRank | References |
3 | 0.43 | 22 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sait Sener | 1 | 11 | 2.36 |
| Mustafa Ünel | 2 | 154 | 20.71 |