Assisting classical paintings restoration : efficient paint loss detection and descriptor-based inpainting using shared pretraining

In the restoration process of classical paintings, one of the tasks is to map paint loss for documentation and analysing purposes. Because this is such a sizable and tedious job automatic techniques are highly on demand. The currently available tools allow only rough mapping of the paint loss areas while still requiring considerable manual work. We develop here a learning method for paint loss detection that makes use of multimodal image acquisitions and we apply it within the current restoration of the Ghent Altarpiece. Our neural network architecture is inspired by a multiscale convolutional neural network known as U-Net. In our proposed model, the downsampling of the pooling layers is omitted to enforce translation invariance and the convolutional layers are replaced with dilated convolutions. The dilated convolutions lead to denser computations and improved classification accuracy. Moreover, the proposed method is designed such to make use of multimodal data, which are nowadays routinely acquired during the restoration of master paintings, and which allow more accurate detection of features of interest, including paint losses. Our focus is on developing a robust approach with minimal user-interference. Adequate transfer learning is here crucial in order to extend the applicability of pre-trained models to the paintings that were not included in the training set, with only modest additional re-training. We introduce a pre-training strategy based on a multimodal, convolutional autoencoder and we fine-tune the model when applying it to other paintings. We evaluate the results by comparing the detected paint loss maps to manual expert annotations and also by running virtual inpainting based on the detected paint losses and comparing the virtually inpainted results with the actual physical restorations. The results indicate clearly the efficacy of the proposed method and its potential to assist in the art conservation and restoration processes

Analyse des orientations éthiques touchant les relations humains-animaux dans les manuels scolaires en ÉCR au primaire

Cette recherche consiste en une analyse des orientations éthiques touchant les relations humains-animaux dans les manuels scolaires approuvés par le Ministère de l’Éducation et de l’Enseignement supérieur pour la mise en œuvre du Programme d’éthique et culture religieuse (PÉCR) dans les écoles primaires du Québec. Pour ce faire, une grille d’analyse a été élaborée à partir d’une clarification conceptuelle de la Humane Education (HE), des positions centrales d’éthique animale (ÉA) et du cadre des Cinq Libertés (5L). Au niveau des résultats, il a été observé que les manuels d’éthique et culture religieuse (ÉCR) destinés aux élèves du primaire présentent des conceptions de l’animal et des relations humains-animaux différenciées selon le type d’utilisation de l’animal. De plus, des ambigüités au niveau des intentions pédagogiques ont pu être soulevées pour certains types d’animaux. Un questionnement éthique envers le traitement des animaux a été relevé à de rares endroits. Aucune des positions d’ÉA n’a été repérée, que ce soit pour les mettre en tension afin que l’élève se fasse son propre jugement ou pour lui donner des repères au sujet de ce domaine de l’éthique de plus en plus présent, autant dans le champ de recherche de l’éthique que dans la société en général. Des éléments des deux courants théoriques majeurs de HE sont pour leur part présents dans les manuels destinés à l’élève. En somme, bien que certains extraits divergent de la tendance générale, la vision de l’animal véhiculée dans les manuels en ÉCR du primaire en éthique et culture religieuse (ÉCR) est basée principalement sur l’utilisation des animaux et cette vision n’est pas remise en question malgré 1. les objectifs de la compétence 1 en ÉCR, nommée « Réfléchir sur des questions éthiques », 2. la présence du thème des besoins des êtres vivants dans le PÉCR et 3. les grandes visées du PÉCR.Abstract: This study consists in an analysis of the ethical orientations regarding the human-animal relations depicted in the textbooks approved by the Ministère de l’Éducation et de l’Enseignement supérieur for the implementation of the Ethics and Religious Culture Program (ERCP) in elementary schools of Quebec. To achieve this, an analysis grid was developed based on a conceptual clarification of Humane Education, central animal ethics (AE) positions and on the Five Freedoms framework. The results show that the Ethics and Religious Culture (ERC) textbooks aimed at elementary school students portray differentiated conceptions of animals and human-animal relations according to the use of the animals. Furthermore, ambiguities regarding the pedagogical intentions were observed for certain types of animals. Ethical reflexions toward the treatment of animals were found in a few rare cases. No AE positions were found, whether to contrast them so that students can use their judgement to form their own opinion or to give students information about this field of ethics that is increasingly present, both in the field of ethics research and in society at large. Elements from both main theoretical currents of HE were found in the textbooks. In summary, while certain passages diverge from the general tendency, the conception of animals portrayed in the ERC textbooks is based primarily on their usage and this conception is not questioned despite 1. the objectives of the competence 1 in ERC, called “to reflect on ethical questions”, 2. the presence of the theme “needs of living beings” in the ERCP and 3. the major aims of the ERCP

Deep learning for paint loss detection with a multiscale, translation invariant network

We explore the potential of deep learning in digital painting analysis to facilitate condition reporting and to support restoration treatments. We address the problem of paint loss detection and develop a multiscale deep learning system with dilated convolutions that enables a large receptive field with limited training parameters to avoid overtraining. Our model handles efficiently multimodal data that are typically acquired in art investigation. As a case study we use multimodal data of the Ghent Altarpiece. Our results indicate huge potential of the proposed approach in terms of accuracy and also its fast execution, which allows interactivity and continuous learning

Object Programming in a Rule-Based Language with Strategies

Colloque avec actes et comité de lecture. internationale.International audienceThis paper presents a programming framework that combines the concepts of objects, rules and strategies, built as an extension of the rule-based language with strategies ELAN. This extension is implemented in a reflective way in ELAN itself and relies on the same formal semantics,namely the rewriting calculus

Digital image processing of the Ghent altarpiece : supporting the painting's study and conservation treatment

In this article, we show progress in certain image processing techniques that can support the physical restoration of the painting, its art-historical analysis, or both. We show how analysis of the crack patterns could indicate possible areas of overpaint, which may be of great value for the physical restoration campaign, after further validation. Next, we explore how digital image inpainting can serve as a simulation for the restoration of paint losses. Finally, we explore how the statistical analysis of the relatively simple and frequently recurring objects (such as pearls in this masterpiece) may characterize the consistency of the painter’s style and thereby aid both art-historical interpretation and physical restoration campaign

Actions & Plans in ELAN

Colloque avec actes sans comité de lecture.ELAN is a declarative language based on rewriting logic. The ELAN language is based on labelled conditional rewrite rules and on strategies for controlling their application. ELAN provides a strategy language to control labelled rules. In this paper we show how to use the ELAN strategy language for planning. We describe how to encode situations and actions and take advantage of ELAN strategies to build plans. We give an example of our approach by describing an elevator controller

Rule Based Programming with Constraints & Strategies

Colloque avec actes et comité de lecture. internationale.International audienceWe present a framework for Rule Based Programming with Constraints and Strategies. It is based on an extension of the ELAN language, that provides an environment for specifying and prototyping deduction systems. The existence of strategies provides the user with the possibility to make choices, to act upon them, and to retract if needed using backtracking. To illustrate the framework, we formalise a planning problem, namely a controller for printing tasks, that shows how to combine rules, strategies and constraint solving on finite domains

An algebraic semantics for objects in a rule-based language

Colloque avec actes et comité de lecture. internationale.International audienceL'acceptation et la participation à ce workshop sont soumises à l'envoi d'un abstract étendu de quelques page