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PhD Defense : Hayat Nasser

October 30, 2018 @ 2:00 pm - 4:00 pm

Hayat Nasser will defend her thesis on Tuesday, October 30th at 2pm in room C005.

Her presentation is entitled “Tools for the analysis of noisy discrete curves”.

Dissertation committee:
Isabelle DEBLED-RENNESSON Professeure des Universités Université de Lorraine Directrice de thèse
Fabien FESCHET Professeur des Universités Université Clermont Auvergne Rapporteur
Eric ANDRES Professeur des Universités Université de Poitiers Rapporteur
Yukiko KENMOCHI Chargée de Recherche Université Paris-Est Examinatrice
Laurent WENDLING Professeur des Universités Université Paris Descartes (Paris V) Examinateur
Salvatore-Antoine TABBONE Professeur des Universités Université de Lorraine Examinateur
Phuc NGO Maître de Conférences Université de Lorraine Examinatrice
Abstract:
In this thesis, we are interested in the study of noisy discrete curves that correspond to the contours of objects in images. We have proposed several tools to analyze them. The dominant points (points whose curvature estimation is locally maximal) play a very important role in pattern recognition and we have developed a non-heuristic, fast and reliable method to detect them in a discrete curve. This method is an improvement of an existing method introduced by Nguyen et al.. The new method consists in calculating a measure of angle. We have also proposed two approaches for polygonal simplification: an automatic method minimizing, and another fixing the vertex number of the resulting polygon.
Then we proposed a new geometric tool, called adaptive tangential cover ATC, based on the detection of meaningful thickness introduced by Kerautret et al.. These thicknesses are calculated at each point of the contours allow to locally estimate the noise level. In this context our construction algorithm of adaptive tangential cover takes into account the different levels of noise present in the curve to be studied and does not require a parameter.
Two applications of ATC in image analysis are proposed: on the one hand the decomposition of the contours of a shape in an image into arcs and right segments and on the other hand, within the framework of a project with an Indian university about the sign language and recognition of hand gestures. Firstly, the method to decompose discrete curves into arcs and straight segments is based on two tools: dominant point detection using adaptive tangential cover and tangent space representation of the polygon issued from detected dominant points. The experiments demonstrate the robustness of the method w.r.t. noise. Secondly, from the outlines of the hands extracted from images taken by a Kinect, we propose several descriptors from the selected dominant points computed from the adaptive tangential cover. The proposed descriptors, which are a combination of statistical descriptors and topological descriptors, are effective and suitable for gesture recognition.

Keywords: Discret geometry, dominant points, tangential cover, polygonal simplification, image processing

Details

Date:
October 30, 2018
Time:
2:00 pm - 4:00 pm
Event Category:

Venue

C005

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