Comparative Evaluation of Random Forest and Fern Classifiers for Real-Time Feature Matching

被引：53

作者：

Barandiaran, Inigo ^{[1
]}

Cottez, Charlote ^{[1
]}

Paloc, Celine ^{[1
]}

Grana, Manuel ^{[2
]}

机构：

[1] VICOMTech, Paseo Mikeletegi 57, San Sebastian 20009, Spain

[2] Univ Basque Country, Comp Sci Sch, San Sebastian 20009, Spain

来源：

WSCG 2008, FULL PAPERS | 2008年

关键词：

Feature matching; Tracking by Detection; Augmented Reality;

D O I：

10.1109/WIAMIS.2008.27

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：159 / +

页数：2

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