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Eric Marchand
Researcher at University of Rennes
Publications - 326
Citations - 7948
Eric Marchand is an academic researcher from University of Rennes. The author has contributed to research in topics: Visual servoing & Robustness (computer science). The author has an hindex of 41, co-authored 308 publications receiving 7113 citations. Previous affiliations of Eric Marchand include Yale University & Université de Sherbrooke.
Papers
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Journal ArticleDOI
Pose Estimation for Augmented Reality: A Hands-On Survey
TL;DR: This paper aims at presenting a brief but almost self-contented introduction to the most important approaches dedicated to vision-based camera localization along with a survey of several extension proposed in the recent years.
Journal ArticleDOI
Real-time markerless tracking for augmented reality: the virtual visual servoing framework
TL;DR: In this paper, nonlinear pose estimation is formulated by means of a virtual visual servoing approach and has been validated on several complex image sequences including outdoor environments.
Journal ArticleDOI
ViSP for visual servoing: a generic software platform with a wide class of robot control skills
TL;DR: A fully functional modular architecture that allows fast development of visual servoing applications, ViSP (Visual Servoing Platform), which takes the form of a library which can be divided in three main modules: control processes, canonical vision-based tasks that contain the most classical linkages, and real-time tracking.
Proceedings ArticleDOI
A real-time tracker for markerless augmented reality
TL;DR: A real-time, robust and efficient 3D model-based tracking algorithm is proposed for a 'video see through' monocular vision system, combining local position uncertainty and global pose uncertainty in an efficient and accurate way by propagating uncertainty.
Journal ArticleDOI
Virtual visual servoing : a framework for real-time augmented reality
Eric Marchand,François Chaumette +1 more
TL;DR: A framework based on the visual servoing approach well known in robotics is proposed, which features simplicity, accuracy, efficiency, and scalability in order to achieve real‐time augmented reality applications.