loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Madjid Maidi ; Fakhr-Eddine Ababsa and Malik Mallem

Affiliation: IBISC Laboratory / CNRS FRE 2873, University of Evry, France

ISBN: 978-972-8865-60-3

Keyword(s): Computer vision, augmented reality, calibration, pose estimation, robust tracking.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Robotics and Automation ; Virtual Environment, Virtual and Augmented Reality ; Vision, Recognition and Reconstruction

Abstract: In this paper, we present a robust fiducials tracking method for real time Augmented Reality systems. Our approach identifies the target object with an internal barecode of the fiducial and extracts its 2D features points. Given the 2D feature points and a 3D object model, object pose consists in recovering the position and the orientation of the object with respect to the camera. For pose estimation, we presented two methods for recovering pose using the Extended Kalman Filter and the Orthogonal Iteration algorithm. The first algorithm is a sequential estimator that predicts and corrects the state vector. While the later uses the object space collinearity error and derives an iterative algorithm to compute orthogonal rotation matrices. Due to lighting or contrast conditions or occlusion of the target object by an other object, the tracking may fail. Therefore, we extend our tracking method using a RANSAC algorithm to deal with occlusions. The algorithm is tested with different camera viewpoints under various image conditions and shows to be accurate and robust. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 52.23.234.7

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Maidi M.; Ababsa F.; Mallem M. and (2006). ROBUST AUGMENTED REALITY TRACKING BASED VISUAL POSE ESTIMATION.In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 346-351. DOI: 10.5220/0001216303460351

@conference{icinco06,
author={Madjid Maidi and Fakhr{-}Eddine Ababsa and Malik Mallem},
title={ROBUST AUGMENTED REALITY TRACKING BASED VISUAL POSE ESTIMATION},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={346-351},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001216303460351},
isbn={978-972-8865-60-3},
}

TY - CONF

JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - ROBUST AUGMENTED REALITY TRACKING BASED VISUAL POSE ESTIMATION
SN - 978-972-8865-60-3
AU - Maidi, M.
AU - Ababsa, F.
AU - Mallem, M.
PY - 2006
SP - 346
EP - 351
DO - 10.5220/0001216303460351

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.