Local geometric consensus : a general purpose point pattern-based tracking algorithm
We present a method which can quickly and robustly match 2D and 3D point patterns based on their sole spatial distribution, but it can also handle other cues if available. This method can be easily adapted to many transformations such as similarity transformations in 2D/3D, and affine and perspectiv...
| Veröffentlicht in: | IEEE transactions on visualization and computer graphics. - 1996. - 21(2015), 11 vom: 01. Nov., Seite 1299-308 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2015
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on visualization and computer graphics |
| Schlagworte: | Journal Article |
| Zusammenfassung: | We present a method which can quickly and robustly match 2D and 3D point patterns based on their sole spatial distribution, but it can also handle other cues if available. This method can be easily adapted to many transformations such as similarity transformations in 2D/3D, and affine and perspective transformations in 2D. It is based on local geometric consensus among several local matchings and a refinement scheme. We provide two implementations of this general scheme, one for the 2D homography case (which can be used for marker or image tracking) and one for the 3D similarity case. We demonstrate the robustness and speed performance of our proposal on both synthetic and real images and show that our method can be used to augment any (textured/textureless) planar objects but also 3D objects |
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| Beschreibung: | Date Completed 04.01.2016 Date Revised 07.10.2015 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0506 |
| DOI: | 10.1109/TVCG.2015.2459897 |