Title
Markerless Outdoor Localisation Based on SIFT Descriptors for Mobile Applications
Abstract
This study proposes augmented reality from mobile devices based on SIFT (Scale Invariant Feature Transform) features for markerless outdoor augmented reality application. The proposed application is navigation help in a city. These SIFT features are projected on a digital model of the building façades of the square to obtain 3D co-ordinates for each feature point. The algorithms implemented calculate the camera pose for frame of a video from 3D-2D point correspondences between features extracted in the current video frame and points in the reference dataset. The algorithms were successfully tested on video films of city squares. Although they do not operate in real-time, they are capable of a correct pose estimation and projection of artificial data into the scene. In case of a loss of track, the algorithms recover automatically. The study shows the potential of SIFT features for purely image based markerless outdoor augmented reality applications. This study takes place in the MoSAIC project.
Year
DOI
Venue
2008
10.1007/978-3-540-69905-7_50
ICISP
Keywords
Field
DocType
feature point,augmented reality,proposed application,video film,mosaic project,markerless outdoor augmented reality,point correspondence,mobile applications,sift descriptors,sift feature,current video frame,markerless outdoor localisation,city square,real time,scale invariant feature transform,pose estimation,sift,feature extraction,mobile device
Computer vision,Scale-invariant feature transform,Pattern recognition,Image matching,Computer science,Image based,Augmented reality,Pose,Mobile device,Artificial intelligence,Content-based image retrieval
Conference
Volume
ISSN
Citations 
5099
0302-9743
1
PageRank 
References 
Authors
0.36
11
4
Name
Order
Citations
PageRank
Frank Lorenz Wendt110.36
Stéphane Bres212714.42
bruno tellez3565.98
Robert Laurini437163.89