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Hybrid tracking approach using optical flow and pose estimation

Muriel Pressigout 1 Eric Marchand 2 Etienne Mémin 3 
2 Lagadic - Visual servoing in robotics, computer vision, and augmented reality
CRISAM - Inria Sophia Antipolis - Méditerranée , Inria Rennes – Bretagne Atlantique , IRISA-D5 - SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE
3 VISTA - Vision spatio-temporelle et active
IRISA - Institut de Recherche en Informatique et Systèmes Aléatoires, Inria Rennes – Bretagne Atlantique
Abstract : This paper proposes an hybrid approach to estimate the 3D pose of an object. The integration of texture information based on image intensities in a more classical non-linear edge-based pose estimation computation has proven to highly increase the reliability of the tracker. We propose in this work to exploit the data provided by an optical flow algorithm for a similar purpose. The advantage of using the optical flow is that it does not require any a priori knowledge on the object appearance. The registration of 2D and 3D cues for monocular tracking is performed by a non linear minimization. Results obtained show that using optical flow enables to perform robust 3D hybrid tracking even without any texture model
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Submitted on : Monday, January 12, 2009 - 10:10:53 AM
Last modification on : Monday, June 27, 2022 - 3:05:58 AM
Long-term archiving on: : Thursday, October 11, 2012 - 3:44:35 PM


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  • HAL Id : inria-00351874, version 1


Muriel Pressigout, Eric Marchand, Etienne Mémin. Hybrid tracking approach using optical flow and pose estimation. IEEE Int. Conf. on Image Processing, ICIP'08, 2008, San Diego, California, France. ⟨inria-00351874⟩



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