Title: | Comparative Evaluation of Random Forest and Fern Classifiers for Real-Time Feature Matching |
Authors: | Barandiaran, Iñigo Cottez, Charlote Paloc, Céline Graña, Manuel |
Citation: | WSCG '2008: Full Papers: The 16-th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision in co-operation with EUROGRAPHICS, University of West Bohemia Plzen, Czech Republic, February 4 - 7, 2008, p. 159-166. |
Issue Date: | 2008 |
Publisher: | Václav Skala - UNION Agency |
Document type: | konferenční příspěvek conferenceObject |
URI: | http://wscg.zcu.cz/wscg2008/Papers_2008/full/!_WSCG2008_Full_final.zip http://hdl.handle.net/11025/10933 |
ISBN: | 978-80-86943-15-2 |
Keywords: | rozpoznávání tvaru;počítačové vidění;rozšířená realita |
Keywords in different language: | feature matching;computer vision;augmented reality |
Abstract: | Feature or keypoint matching is a critical task in many computer vision applications, such as optical 3D reconstruction or optical markerless tracking. These applications demand very accurate and fast matching techniques. We present an evaluation and comparison of two keypoint matching strategies based on supervised classification for markerless tracking of planar surfaces. We have applied these approaches on an augmented reality prototype for indoor and outdoor design review. |
Rights: | © Václav Skala - UNION Agency |
Appears in Collections: | WSCG '2008: Full Papers |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Barandiaran.pdf | Plný text | 1,4 MB | Adobe PDF | View/Open |
Barandiaran.ppt | Prezentace | 8,26 MB | Microsoft Powerpoint | View/Open |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/10933
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