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Dive into the research topics where Georges Younes is active.

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Featured researches published by Georges Younes.


Robotics and Autonomous Systems | 2017

Keyframe-based monocular SLAM

Georges Younes; Daniel C. Asmar; Elie A. Shammas; John S. Zelek

Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframe-based monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery. A general guideline for the design of a Keyframe-based monocular SLAM.A survey on all Keyframe-based monocular SLAM (KSLAM) systemsInsight into the current state of KSLAM and future directions


Journal of Electronic Imaging | 2016

Pose tracking for augmented reality applications in outdoor archaeological sites

Georges Younes; Daniel C. Asmar; Imad H. Elhajj; Howayda Al-Harithy

Abstract. In recent years, agencies around the world have invested huge amounts of effort toward digitizing many aspects of the world’s cultural heritage. Of particular importance is the digitization of outdoor archaeological sites. In the spirit of valorization of this digital information, many groups have developed virtual or augmented reality (AR) computer applications themed around a particular archaeological object. The problem of pose tracking in outdoor AR applications is addressed. Different positional systems are analyzed, resulting in the selection of a monocular camera-based user tracker. The limitations that challenge this technique from map generation, scale, anchoring, to lighting conditions are analyzed and systematically addressed. Finally, as a case study, our pose tracking system is implemented within an AR experience in the Byblos Roman theater in Lebanon.


Journal of Computational Vision and Imaging Systems | 2016

Road Defect Detection in Street View Images using Texture Descriptors and Contour Maps

David Abou Chacra; Henry Leopold; Jeremy Pinto; Norman Lunscher; Georges Younes; John S. Zelek

Road quality assessment is a crucial part in municipalities’ work to maintain their infrastructure, plan upgrades, and manage their budgets. Properly maintaining this infrastructure relies heavily on consistently monitoring its condition and deterioration over time. This can be a challenge, especially in larger towns and cities where there is a lot of city property to keep an eye on. We review road quality assessment methods currently employed, and then describe our novel algorithm aimed at identifying distressed road regions from street view images and pinpointing cracks within them. We predict distressed regions by computing Fisher vectors on local SIFT descriptors and classifying them with an SVM trained to distinguish between road qualities. We follow this step with a comparison to a weighed contour map within these distressed regions to identify exact crack and defect locations, and use the contour weights to predict the crack severity. Promising results are obtained on our manually annotated dataset, which indicate the viability of using this cost-effective system to perform road quality assessment at a municipal level.


Archive | 2013

Efficient Suturing of Deformable Models

Georges Younes; Julien Abi-Nahed; George Turkiyyah

Suturing is a fundamental operation in surgical procedures. Simulation of suturing involves the simulation of needle–tissue and thread–tissue interaction, as well as contact between sutured boundaries. In this work, robust methods are proposed for an efficient finite element-based suture simulation. Contact conditions are modeled using complementarity relations. By exploiting adjacency relationships inherent to simplicial meshes and decomposing rigid body motion into sliding and bulk-deforming components, needle driving can be simulated in real time without introducing any new mesh elements. In addition, a computationally efficient formulation of thread pulling is presented. These techniques are implemented and tested in a prototype system which allows for interactive simulation of suturing with high resolution models.


Digital Applications in Archaeology and Cultural Heritage | 2017

Virtual and augmented reality for rich interaction with cultural heritage sites: A case study from the Roman Theater at Byblos

Georges Younes; Rany Kahil; Mayssa Jallad; Daniel C. Asmar; Imad H. Elhajj; George Turkiyyah; Howayda Al-Harithy


arXiv: Computer Vision and Pattern Recognition | 2016

A survey on non-filter-based monocular Visual SLAM systems.

Georges Younes; Daniel C. Asmar; Elie A. Shammas


arXiv: Computer Vision and Pattern Recognition | 2018

FDMO: Feature Assisted Direct Monocular Odometry.

Georges Younes; Daniel C. Asmar; John S. Zelek


Qatar Foundation Annual Research Conference Proceedings | 2016

Clustering of Medical Images for Analysis: A Fuzzy Approach

Sarada Prasad Dakua; Nikhil V. Navkar; Julien Abinahed; Georges Younes; Abdulla Al-Ansari


Journal of Computational Vision and Imaging Systems | 2016

IR Shape From Shading Enhanced RGBD for 3D Scanning

Nolan Lunscher; Georges Younes; David Abou Chacra; Henry Leopold; Jeremy Pinto; John S. Zelek


Journal of Computational Vision and Imaging Systems | 2016

Spatial Detection of Vehicles in Images using Convolutional Neural Networks and Stereo Matching

Jeremy Pinto; Nolan Lunscher; Georges Younes; David Abou Chacra; Henry Leopold; John S. Zelek

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Daniel C. Asmar

American University of Beirut

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George Turkiyyah

American University of Beirut

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Elie A. Shammas

American University of Beirut

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Howayda Al-Harithy

American University of Beirut

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Imad H. Elhajj

American University of Beirut

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Mayssa Jallad

American University of Beirut

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Rany Kahil

American University of Beirut

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