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Contribution à la perception visuelle multi-résolution de l’environnement 3D : application à la robotique autonome

Abstract : The research work, carried out within the framework of this thesis, concerns the development of a system of perception and saliency detection in 3D environment taking advantage from a pseudo-3D representation. Our contribution and the issued concept derive from the hypothesis that the depth of the object with respect to the robot is an important factor in the detection of the saliency. On this basis, a salient vision system of the 3D environment has been proposed, designed and validated on a platform including a robot equipped with a pseudo-3D sensor. The implementation of the aforementioned concept and its design were first validated on the pseudo-3D KINECT vision system. Then, in a second step, the concept and the algorithms have been extended to the aforementioned robotic platform. The main contributions of the present thesis can be summarized as follow: A) A state of the art on the various sensors for acquiring depth information as well as different methods of detecting 2D salience and pseudo 3D. B) Study of pseudo-3D visual saliency system based on benefiting from the development of a robust algorithm allowing the detection of salient objects. C) Implementation of a depth estimation system in centimeters for the Pepper robot. D) Implementation of the concepts and methods proposed on the aforementioned platform. The carried out studies and the experimental validations confirmed that the proposed approaches allow to increase the autonomy of the robots in a real 3D environment
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Submitted on : Tuesday, May 15, 2018 - 3:28:06 PM
Last modification on : Sunday, September 27, 2020 - 5:27:11 AM
Long-term archiving on: : Monday, September 24, 2018 - 2:44:43 PM


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  • HAL Id : tel-01792544, version 1



Hossam Fraihat. Contribution à la perception visuelle multi-résolution de l’environnement 3D : application à la robotique autonome. Traitement du signal et de l'image [eess.SP]. Université Paris-Est, 2017. Français. ⟨NNT : 2017PESC1065⟩. ⟨tel-01792544⟩



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