Paper Info
Title
PTrack: Introducing a Novel Iterative Geometric Pose Estimation for a Marker-based Single Camera Tracking System
Abstract
to present a challenge in terms of performance, robustness and accuracy. In particular mobile augmented reality applications are in need of tracking systems which can be wearable and do not cause a high processing load. In this paper we introduce a novel iterative geometric method for pose estimation from four co-planar points and we present the current status of PTrack, a marker-based single camera tracking system benefiting from this approach. The system uses an IDS uEye [1] camera, equipped with infrared flash strobes and infrared pass filter, which acquires grayscale images and sends them to a computer where an image pre-processing algorithm identifies potential projections of retro-reflective markers. Our novel pose estimation algorithm identifies possible labels composed of markers in a 2D post-processing using a divide-and-conquer strategy to segment the camera's image space and attempts an iterative geometric 3D reconstruction of position and orientation in camera space. In the end successfully reconstructed labels are compared to a database for identification. Their 6 DoF data as well as their ID is made available to applications through OpenTracker [2] framework. To assess the performance of our approach we compared PTrack to ARToolKit [3] - which has been adapted to work with the same camera - and final results show that pose estimation is more accurate and precise, in both translation and rotation.
Year
DOI
Venue
2006
10.1109/VR.2006.114
VR
Keywords
Field
DocType
ids ueye,image space,infrared pass filter,infrared flash strobes,novel iterative geometric pose,dof data,novel iterative geometric method,camera space,marker-based single camera tracking,grayscale image,estimation algorithm,gray scale,divide and conquer,pose estimation,augmented reality,iterative methods,3d reconstruction,intrusion detection,image reconstruction,robustness,infrared,tracking system,virtual reality
Computer vision,Wearable computer,Computer science,Simulation,3D pose estimation,Tracking system,Robustness (computer science),Augmented reality,Pose,Artificial intelligence,Grayscale,3D reconstruction
Conference
ISSN
ISBN
Citations 
1087-8270
1-4244-0224-7
11
PageRank 
References 
Authors
0.93
5
4
Name
Order
Citations
PageRank
Pedro Santos18021.90
Andre Stork210711.13
Alexandre Buaes3232.68
Joaquim Jorge413111.06