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Robust Fiducials Tracking in Augmented Reality

Abstract : In this paper, we present a robust fiducials tracking method for real time Augmented Reality systems. We use a generic algorithm for object detection and feature points extraction, then, we identify the target object with its barcode for template matching. Given a 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. Using the computed pose and the identified object, we propose a first tracking algorithm based on homography computation. However due to lighting or contrast conditions or occlusion of the target object by an other object, the tracking may fail. Therefore, we extend the previous object pose algorithm for bar-coded fiducials, using a second algorithm based on RANSAC estimator and fiducial reprojection on the image. The proposed method is computationally efficient and showed to be accurate and robust.
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Contributor : Frédéric Davesne Connect in order to contact the contributor
Submitted on : Tuesday, November 18, 2008 - 2:26:03 AM
Last modification on : Tuesday, February 8, 2022 - 4:34:02 PM


  • HAL Id : hal-00339471, version 1



Madjid Maidi, Fakhr-Eddine Ababsa, Malik Mallem. Robust Fiducials Tracking in Augmented Reality. 13th IEEE International Conference on Systems, Signals and Image Processing (IWSSIP 2006), 2006, Budapest, Hungary. pp.ERREUR_CHAMPS_NON_SPECIFIE. ⟨hal-00339471⟩



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