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Estimation du regard avec une caméra RGB-D dans des environnements utilisateur non-contraints

Abstract : In this thesis, we tackled the automatic gaze estimation problem in unconstrained user environments. This work takes place in the computer vision research field applied to the perception of humans and their behaviors. Many existing industrial solutions are commercialized and provide an acceptable accuracy in gaze estimation. These solutions often use a complex hardware such as range of infrared cameras (embedded on a head mounted or in a remote system) making them intrusive, very constrained by the user's environment and inappropriate for a large scale public use. We focus on estimating gaze using cheap low-resolution and non-intrusive devices like the Kinect sensor. We develop new methods to address some challenging conditions such as head pose changes, illumination conditions and user-sensor large distance. In this work we investigated different gaze estimation paradigms. We first developed two automatic gaze estimation systems following two classical approaches: feature and semi appearance-based approaches. The major limitation of such paradigms lies in their way of designing gaze systems which assume a total independence between eye appearance and head pose blocks. To overcome this limitation, we converged to a novel paradigm which aims at unifying the two previous components and building a global gaze manifold, we explored two global approaches across the experiments by using synthetic and real RGB-D gaze samples.
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Submitted on : Thursday, January 25, 2018 - 6:10:08 PM
Last modification on : Wednesday, October 14, 2020 - 3:52:59 AM
Long-term archiving on: : Friday, May 25, 2018 - 7:49:17 AM


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  • HAL Id : tel-01693122, version 1


Amine Kacete. Estimation du regard avec une caméra RGB-D dans des environnements utilisateur non-contraints. Autre. CentraleSupélec, 2016. Français. ⟨NNT : 2016CSUP0012⟩. ⟨tel-01693122⟩



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