SHREC’20 Track:Retrieval of digital surfaces with similar geometric reliefs

International audienceThis paper presents the methods that have participated in the SHREC'20 contest on retrieval of surface patches with similar geometric reliefs and 1 the analysis of their performance over the benchmark created for this challenge. The goal of the context is to verify the possibility of retrieving 3D models only based on the reliefs that are present on their surface and to compare methods that are suitable for this task. This problem is related to many real world applications, such as the classification of cultural heritage goods or the analysis of different materials. To address this challenge, it is necessary to characterize the local "geometric pattern" information, possibly forgetting model size and bending. Seven groups participated in this contest and twenty runs were submitted for evaluation. The performances of the methods reveal that good results are achieved with a number of techniques that use different approaches

Imagerie RTI adaptative : Acquisition, Automatisation et mosaïcage.

Reflectance Transformation Imaging (RTI) is a digital imaging technique that captures the way a surface reflects light coming from different angles. It is commonly used to study cultural heritage artifacts, such as ancient manuscripts, coins and sculptures, because it can reveal detailed surface features that may not be visible under ambient light. RTI works by capturing a series of images of an object being illuminated from different points on a hemisphere or dome. These images are then combined using specialized software to create a single, high-resolution image that encodes the surface's reflectance properties. The resulting RTI image can then be interactively visualized on a computer, allowing the user to adjust virtually the lighting direction to highlight different features of the surface.Acquisition, modeling, and visualization of reflectance of complex surfaces is still an active area of research in the RTI field. Complex surfaces can include objects with varying size, shape, material properties, which require specialized and adaptive techniques to accurately capture their reflectance properties. In this thesis, we have focused on addressing the challenges in realizing surface adaptive RTI and automating the acquisition process. We have developed methods for estimating the optimal light configuration for capturing RTI sequence adaptive to the surface being digitized. We also developed methods for stitching together multiple RTI data sets and thus improve the resolution of the RTI data. These methods are developed to improve the accuracy and efficiency of surface adaptive RTI, and to bring advances in the field of digital imaging for cultural heritage and applications. In the current state of the art, RTI acquisitions are typically carried out by manual placement of a light at different directions (free form) or use of RTI domes with fixed light positions or mechanized dome with movable light source to capture a series of images. Manually positioning the light source is a time-consuming process and lacks accuracy, repeatability. RTI domes are efficient and more reliable, however they are limited to acquisition of smaller sized objects only. To address the limitations pertaining to free form and the dome systems, we investigated the use of robotic arm and automation to streamline the RTI acquisition process. This involves the use of robotic arm to position the light source, use of a XY stage to position the surface as well as automated image capture systems. There are several benefits to automating RTI acquisition. One advantage is the ability to capture RTI images of large surfaces that are generally difficult (or impossible) to acquire using RTI domes. There are several challenges associated with the automation of RTI acquisition process using robotic arm and XY platform such as building the control systems that can accurately and reliably position the light aligning it to the required angles, collision avoidance in robotic arm planning, integration of these systems into a cohesive and user-friendly workflow, ensuring that the resulting RTI images are of high quality and meet the needs of the user. We studied these challenges in our work, built a fully functional novel robotic arm-based acquisition system and demonstrated the advantage of this system over the other existing systems.Le Reflectance Transformation Imaging (RTI) est une technique d'imagerie mesurant la réflectance angulaire locale des surfaces en variant l'angle d'éclairage. Utilisée pour étudier le patrimoine culturel, elle révèle des attributs de surface invisibles à l'œil nu ou à la lumière ambiante. Le RTI capture des images d'un objet éclairé sous différents angles sur un hémisphère ou un dôme. Les images sont combinées pour créer une seule image haute résolution codant les propriétés de réflectance de la surface. L'image RTI résultante est visualisable et ajustable virtuellement pour mettre en évidence des caractéristiques de surface. L'acquisition, la modélisation et la visualisation de la réflectance des surfaces complexes sont un domaine de recherche actif. Pour cela, nous avons développé des méthodes d'acquisition RTI adaptative et d'automatisation. Nous avons estimé la configuration d'éclairage optimale et amélioré la résolution des données RTI par assemblage. Ces avancées visent à améliorer l'efficacité de la RTI et l'imagerie numérique du patrimoine culturel. Les acquisitions RTI sont généralement manuelles ou utilisent des dômes RTI, mais nous avons exploré l'utilisation de bras robotiques et d'automatisation pour capturer des surfaces plus grandes. Les défis incluent le positionnement précis de la lumière, l'évitement de collisions, l'intégration fluide des systèmes et la qualité des images RTI. Nous avons étudié ces défis, développé un système d'acquisition robotique novateur et démontré ses avantages

Next Best Light Position: A self configuring approach for the Reflectance Transformation Imaging acquisition process

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A Benchmark Dataset and Evaluation for Best Light Configuration in Reflectance Transformation Imaging

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Extended Framework for Multispectral RTI

International audienceReflectance transformation imaging (RTI) is a widespread technique for studying and documenting cultural heritage artifacts encompassing textural information. The principle is capturing an object from a static camera position by changing the direction of the incident light in each image. The coupling of this approach with multispectral imaging (Multispectral RTI) has shown promising results in the recent years. Considering this approach, we propose an expanded framework for the investigation and documentation of the visual appearance of surfaces, targeted to cultural heritage artifacts. In this work, we study the integrated representation of the angular and spectral components of reflectance, as well as the contributions of exploration by independent wavelengths

LightBot: A Multi-Light Position Robotic Acquisition System for Adaptive Capturing of Cultural Heritage Surfaces

Multi-light acquisitions and modeling are well-studied techniques for characterizing surface geometry, widely used in the cultural heritage field. Current systems that are used to perform this kind of acquisition are mainly free-form or dome-based. Both of them have constraints in terms of reproducibility, limitations on the size of objects being acquired, speed, and portability. This paper presents a novel robotic arm-based system design, which we call LightBot, as well as its applications in reflectance transformation imaging (RTI) in particular. The proposed model alleviates some of the limitations observed in the case of free-form or dome-based systems. It allows the automation and reproducibility of one or a series of acquisitions adapting to a given surface in two-dimensional space

A robust robot design for item picking

In order to build a stable and reliable system for the Amazon Robotics Challenge we went through a detailed study of the performance and system requirements based on the rules and our past experience of the challenge. The challenge was to build a robot that integrates grasping, vision, motion planning, among others, to be able to pick items from a shelf to specific order boxes. This paper presents the development process including component selection, module designs, and deployment. The resulting robot system has dual 6 degrees of freedom industrial arms mounted on fixed bases, which in turn are mounted on a calibrated table. The robot works with a custom-designed top-open extendable shelf. The vision system uses multiple stereo cameras mounted on a fixed calibrated frame. Feature-based comparison and machine-learning based matching are used to identify and determine item pose. The gripper system uses suction cup and the grasping strategy is pick from the top. Error recovery strategies were also implemented to ensure robust performance. During the competition, the robot was able to pick all target items with the shortest amount of time.NRF (Natl Research Foundation, S’pore)ASTAR (Agency for Sci., Tech. and Research, S’pore)Accepted versio

: Diaporama commun des présentations

International audienceLe 11 mars 2024 a eu lieu la première journée des doctorants des sciences du numérique (JDSN) organisée par les doctorants du LIB.Sur le temps d’un après-midi, plusieurs intervenants ont pu faire découvrir aux étudiants de master et de Polytech Dijon le doctorat et les métiers de la recherche. La demi-journée s’est orientée autour de deux questions majeures :– qu’est-ce qu’un doctorat ?– quelles sont les thématiques de recherche des sciences du numérique ?Pour apporter des éléments de réponse à la première question, une présentation et une table ronde ont été animées par Candice Chaillou du Collège Doctoral UBFC. La présentation a d’abord permis de mettre en avant les motivations, le fonctionnement, les compétences acquises et les opportunités de carrière offertes par un doctorat. La table ronde a ensuite fourni l’opportunité de confronter la théorie à la pratique au travers de témoignages et de retours d’expérience de 4 doctorants des laboratoires bourguignons LIB et ImViA : Boris Bordeaux, Houda Rafi, Maëlle Beuret et Alexis Guyot. Les doctorants interrogés ont pu revenir sur leur parcours, sur les spécificités apportées par leurs financements et sur leur quotidien en tant que doctorants. La table ronde a également été l’occasion de répondre aux questions des étudiants de l’auditoire par rapport au doctorat.Pour apporter des éléments de réponse à la seconde question, 13 doctorants, 1 post-doctorant et 2 ingénieurs des laboratoires LIB et ImViA ont présenté leurs travaux de recherche au travers de présentations courtes et vulgarisées de 5 minutes. Un grand nombre de thématiques des sciences du numérique ont ainsi pu être mises en lumière :– Alexis GUYOT, doctorant au LIB – Robustesse des analyses sur les données massives dans les lacs de données : une approche fonctionnelle– David CAMARAZO, doctorant au LIB – Interopérabilité sémantique du processus de modélisation des systèmes ferroviaires– Selsebil BENELHAJ, doctorante au LIB – Approche IA pour la caractérisation d’un logement ou d’un bâtiment par rapport aux contraintes réglementaires associées– Sébastien GUILLEMIN, doctorant au LIB – Interprétation de données hétérogènes et multivariées– Hugo CASTANEDA, ingénieur ImViA – Multimodalité : l’assemblée des IA pour unir les savoirs– Sean MAROTTA, ingénieur ImViA – Réseaux de neurones sur cibles embarquées– Abdelhamid GARAH, doctorant au LIB – Gestion autonome des services de sécurité dans l’internet des objets– Kévin SECRET-MORLAND, doctorant ImViA – Appariement des surfaces pour l’assemblage ou la reconnaissance d’objets 3D pour l’archéologie– Ibrahim DIARRA, doctorant au LIB – Caractérisation de maillages issue de données archéologiques– Clément POULL, doctorant au LIB – Modélisation, génération et caractérisation géométrique de surfaces rugueuses– Boris BORDEAUX, doctorant au LIB – Conception de structures lacunaires fractales– Mahya FARAJI, doctorante ImViA – Localisation automatique des zones responsables de la tachycardie ventriculaire– Ramamoorthy LUXMAN, post-doctorant ImViA – Reflectance Transformation Imaging – Acquisition, Automation and Stitching– Florian SCALVINI, doctorant ImViA – Méthode et système d’assistance à la navigation de personnes basés sur la perception sonore d’une scène visuelle– Houda RAFI, doctorante ImViA – Objectivation du ressenti conducteur dans les ADAS et la liaison au sol– Maëlle BEURET, doctorante au LIB – COBAI, un modèle à base d’agents pour les comportements humainsEnfin, deux moments conviviaux au milieu et à la fin de l’après-midi ont permis aux étudiants, doctorants, post-doctorants, ingénieurs et enseignants-chercheurs présents d’échanger entre eux sur les différents aspects abordés lors de cette journée.Le LIB remercie les étudiants et les différents intervenants de cette journée pour leur participation, l’école doctorale SPIM pour le financement des déplacements des doctorants hors-site et l’école d’ingénieurs Polytech Dijon pour le prêt de ses locaux et de son matériel