Connoisseur : análise de procedência em pinturas

Orientador: Anderson de Rezende RochaDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O crescimento de arte no meio digital tem, sem sombras de dúvida, democratizado o acesso ao conteúdo pelo público em geral. Entretanto, esse crescimento também implicou no indesejado aumento no número de falsificações e desinformação sobre conteúdos acerca de arte. Nesta linha, aprendizado de máquina pode ser utilizado para automatizar a organização e identificação de obras de arte em relação à sua providência, auxiliando especialistas e usuários comuns na obtenção e validação de obras de arte. Empregamos neste trabalho estratégias baseadas em redes convolucionais para identificar e classificar artefatos digitais relacionados à arte. Primeiramente, pinturas de van Gogh são usadas para explorar e refinar estratégias capazes de discriminar seus padrões de pincelada. Múltiplos testes de conjuntos de dados cruzados são executados a fim de validar o método mais promissor encontrado. Os resultados indicam que atingimos uma drástica melhora em performance enquanto produzindo uma leve melhora em pontuação (90.99% acurácia em nível de segmento de pintura, 95.52% acurácia em nível de pinturas), quando comparado à estudos anteriores sobre o mesmo conjunto de dados. Estendendo nosso trabalho a partir da análise sobre van Gogh para um maior escopo, consideramos o conjunto de dados Painter by Numbers, onde expandimos nossa estratégia para o cenário multi-classe, onde buscamos distinguir pinturas divididas em 1.584 diferentes autores, 135 estilos e 42 gêneros. Propomos um método que combina informação dos três grupos de classes em um único discriminador de autoria, atingindo a ROC AUC competitiva de 0.91361 sem a aplicação de transformações potencialmente destrutivas sobre os padrões de pincelada que poderiam salientar características artificiais adjacentes, como brilho, contraste, escalas e objetosAbstract: Increasing digital art has without a doubt democratized the access to art content to the public at large. It has had, however, resulted in an inadvertent growing number of forgeries and misinformation around art content. In this vein, machine learning can be used to automatically organize and identify art content with respect to its provenance, aiding experts and regular users to retrieve and validate art pieces. In this work, we employ convolutional networks-based strategies to identify and classify art-related digital artifacts. Firstly, van Gogh paintings are used to explore and refine strategies capable of discriminating the brushstroke pattern of van Gogh. Multiple cross-dataset tests are performed in order to further validate the most promising method. We achieve significant performance improvements while slightly increasing accuracy (91% patch-level, 95.5% sample-level) when compared to previous studies in the same dataset. Extending our work from van Gogh analyses to a much broader setup, we consider the Painter by Numbers dataset, in which we expand our strategy to a multi-class scenario, seeking to distinguish paintings from 1,584 different authors, 135 art styles and 42 genres. We propose a method that combines information from these three class-groups into a single authorship discriminator, achieving the competitive ROC AUC of 0.91 without any transformations that could potentially damage the brushstroke patterns and emphasize adjacent features, such as brightness, contrast, scales and objectsMestradoCiência da ComputaçãoMestre em Ciência da Computação137446/2016-0CNP

Statistical analysis and transfer of coarse-grain pictorial style

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 96-103).We show that image statistics can be used to analyze and transfer simple notions of pictorial style of paintings and photographs. We characterize the frequency content of pictorial styles, such as multi-scale, spatial variations, and anisotropy properties, using a multi-scale and oriented decomposition, the steerable pyramid. We show that the average of the absolute steerable coefficients as a function of scale characterizes simple notions of "look" or style. We extend this approach to account for image non-stationarity, that is, we capture and transfer the spatial variations of multi-scale content. In addition, we measure the standard deviation of the steerable coefficients across orientation, which characterizes image anisotropy and permits analysis and transfer of oriented structures. We focus on the statistical features that can be transferred. Since we couple analysis and transfer, our statistical model and transfer tools are consistent with the visual effect of pictorial styles. For this reason, our technique leads to more intuitive manipulation and interpolation of pictorial styles. In addition, our statistical model can be used to classify and retrieve images by style.by Soonmin Bae.S.M

Aiding the conservation of two wooden Buddhist sculptures with 3D imaging and spectroscopic techniques

The conservation of Buddhist sculptures that were transferred to Europe at some point during their lifetime raises numerous questions: while these objects historically served a religious, devotional purpose, many of them currently belong to museums or private collections, where they are detached from their original context and often adapted to western taste. A scientific study was carried out to address questions from Museo d'Arte Orientale of Turin curators in terms of whether these artifacts might be forgeries or replicas, and how they may have transformed over time. Several analytical techniques were used for materials identification and to study the production technique, ultimately aiming to discriminate the original materials from those added within later interventions

Navigating the roadblocks to spectral color reproduction: data-efficient multi-channel imaging and spectral color management

Commercialization of spectral imaging for color reproduction will require the identification and traversal of roadblocks to its success. Among the drawbacks associated with spectral reproduction is a tremendous increase in data capture bandwidth and processing throughput. Methods are proposed for attenuating these increases with data-efficient methods based on adaptive multi-channel visible-spectrum capture and with low-dimensional approaches to spectral color management. First, concepts of adaptive spectral capture are explored. Current spectral imaging approaches require tens of camera channels although previous research has shown that five to nine channels can be sufficient for scenes limited to pre-characterized spectra. New camera systems are proposed and evaluated that incorporate adaptive features reducing capture demands to a similar few channels with the advantage that a priori information about expected scenes is not needed at the time of system design. Second, proposals are made to address problems arising from the significant increase in dimensionality within the image processing stage of a spectral image workflow. An Interim Connection Space (ICS) is proposed as a reduced dimensionality bottleneck in the processing workflow allowing support of spectral color management. In combination these investigations into data-efficient approaches improve two critical points in the spectral reproduction workflow: capture and processing. The progress reported here should help the color reproduction community appreciate that the route to data-efficient multi-channel visible spectrum imaging is passable and can be considered for many imaging modalities

Analyse et recherche d'oeuvres d'art 2D selon le contenu pictural

État de l'art des méthodes manuelles et automatiques d'analyse des oeuvres d'art 2D -- Recherche d'images selon l'organisation spatiale des couleurs -- Seuil automatique pour la recherche d'images selon l'OSC -- Extraction des contours des traits -- Analyse de l'impact pictural dans les oeuvres au trait -- Conclusion et perspectives

TECHNART 2017. Non-destructive and microanalytical techniques in art and cultural heritage. Book of abstracts

440 p.TECHNART2017 is the international biannual congress on the application of Analytical Techniques in Art and Cultural Heritage. The aim of this European conference is to provide a scientific forum to present and promote the use of analytical spectroscopic techniques in cultural heritage on a worldwide scale to stimulate contacts and exchange experiences, making a bridge between science and art. This conference builds on the momentum of the previous TECHNART editions of Lisbon, Athens, Berlin, Amsterdam and Catania, offering an outstanding and unique opportunity for exchanging knowledge on leading edge developments. Cultural heritage studies are interpreted in a broad sense, including pigments, stones, metal, glass, ceramics, chemometrics on artwork studies, resins, fibers, forensic applications in art, history, archaeology and conservation science. The meeting is focused in different aspects: - X-ray analysis (XRF, PIXE, XRD, SEM-EDX). - Confocal X-ray microscopy (3D Micro-XRF, 3D Micro-PIXE). - Synchrotron, ion beam and neutron based techniques/instrumentation. - FT-IR and Raman spectroscopy. - UV-Vis and NIR absorption/reflectance and fluorescence. - Laser-based analytical techniques (LIBS, etc.). - Magnetic resonance techniques. - Chromatography (GC, HPLC) and mass spectrometry. - Optical imaging and coherence techniques. - Mobile spectrometry and remote sensing

A Social Dimension for Digital Architectural Practice

Merged with duplicate record 10026.1/1296 on 14.03.2017 by CS (TIS)This thesis proceeds from an analysis of practice and critical commentary to claim that the opportunities presented to some architectural practices by the advent of ubiquitous digital technology have not been properly exploited. The missed opportunities, it claims, can be attributed largely to the retention of a model of time and spaces as discrete design parameters, which is inappropriate in the context of the widening awareness of social interconnectedness that digital technology has also facilitated. As a remedy, the thesis shows that some social considerations essential to good architecture - which could have been more fully integrated in practice and theory more than a decade ago - can now be usefully revisited through a systematic reflection on an emerging use of web technologies that support social navigation. The thesis argues through its text and a number of practical projects that the increasing confidence and sophistication of interdisciplinary studies in geography, most notably in human geography, combined with the technological opportunities of social navigation, provide a useful model of time and space as a unified design parameter. In so doing the thesis suggests new possibilities for architectural practices involving social interaction. Through a literature review of the introduction and development of digital technologies to architectural practice, the thesis identifies the inappropriate persistence of a number of overarching concepts informing architectural practice. In a review of the emergence and growth of 'human geography' it elaborates on the concept of the social production of space, which it relates to an analysis of emerging social navigation technologies. In so doing the thesis prepares the way for an integration of socially aware architecture with the opportunities offered by social computing. To substantiate its claim the thesis includes a number of practical public projects that have been specifically designed to extend and amplify certain concepts, along with a large-scale design project and systematic analysis which is intended to illustrate the theoretical claim and provide a model for further practical exploitation

Intelligence, Creativity and Fantasy

UID/HIS/04666/2019 This is the 2nd volume of PHI series, published by CRC Press, the 4th published by CRC Press and the 5th volume of PHI proceedings.The texts presented in Proportion Harmonies and Identities (PHI) - INTELLIGENCE, CREATIVITY AND FANTASY were compiled with the intent to establish a multidisciplinary platform for the presentation, interaction and dissemination of research. The aim is also to foster the awareness and discussion on the topics of Harmony and Proportion with a focus on different visions relevant to Architecture, Arts and Humanities, Design, Engineering, Social and Natural Sciences, and their importance and benefits for the sense of both individual and community identity. The idea of modernity has been a significant motor for development since the Western Early Modern Age. Its theoretical and practical foundations have become the working tools of scientists, philosophers, and artists, who seek strategies and policies to accelerate the development process in different contexts.authorsversionpublishe

Art, art history and systems-theory

Foreword on p.