Name
Abstract | ||
|---|---|---|
In this work we present a novel idea of evaluating natural feature-point based tracking targets. Our main objective is to evaluate the inherent characteristics of natural feature-point sets with respect to vision-based pose estimation algorithms. Our work attempts to break new ground by concentrating on evaluating complete tracking targets, rather than evaluating tracking methods or single features. This allows deriving indications on how to improve the trackability of natural feature point sets. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ISMAR.2009.5336469 | ISMAR |
Keywords | Field | DocType |
tracking method,inherent characteristic,natural feature-point,natural feature-point set,work attempt,natural feature point set,complete tracking target,new ground,main objective,estimation algorithm,computer vision,feature extraction,pose estimation,lighting,augmented reality,computational modeling,pipelines | Computer vision,Computer science,Augmented reality,Feature extraction,Pose,Artificial intelligence,Machine learning | Conference |
ISSN | Citations | PageRank |
1554-7868 | 2 | 0.66 |
References | Authors | |
6 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lukas Gruber | 1 | 102 | 7.88 |
| Stefanie Zollmann | 2 | 227 | 22.58 |
| Daniel Wagner | 3 | 1274 | 85.03 |
| Dieter Schmalstieg | 4 | 4169 | 332.77 |