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Dense non-rigid visual tracking with a robust similarity function

Bertrand Delabarre 1 Eric Marchand 1 
1 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
Abstract : This paper deals with dense non-rigid visual tracking robust towards global illumination perturbations of the observed scene. The similarity function is based on the sum of condi- tional variance (SCV). With respect to most approaches that minimize the sum of squared differences, which is poorly robust towards illumination variations in the scene, the choice of SCV as our registration function allows the approach to be naturally robust towards global perturbations. Moreover, a thin-plate spline warping function is considered in order to take into account deformations of the observed template. The proposed approach, after being detailed, is tested in nominal conditions and on scenes where light perturbations occur in order to assess the robustness of the approach.
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Submitted on : Wednesday, May 28, 2014 - 9:43:40 AM
Last modification on : Thursday, January 20, 2022 - 4:20:28 PM
Long-term archiving on: : Thursday, August 28, 2014 - 11:10:50 AM


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  • HAL Id : hal-00997377, version 1


Bertrand Delabarre, Eric Marchand. Dense non-rigid visual tracking with a robust similarity function. IEEE Int. Conf. on Image Processing, ICIP'14, Oct 2014, Paris, France. ⟨hal-00997377⟩



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