1,228 research outputs found

    Deep Reflectance Maps

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    Undoing the image formation process and therefore decomposing appearance into its intrinsic properties is a challenging task due to the under-constraint nature of this inverse problem. While significant progress has been made on inferring shape, materials and illumination from images only, progress in an unconstrained setting is still limited. We propose a convolutional neural architecture to estimate reflectance maps of specular materials in natural lighting conditions. We achieve this in an end-to-end learning formulation that directly predicts a reflectance map from the image itself. We show how to improve estimates by facilitating additional supervision in an indirect scheme that first predicts surface orientation and afterwards predicts the reflectance map by a learning-based sparse data interpolation. In order to analyze performance on this difficult task, we propose a new challenge of Specular MAterials on SHapes with complex IllumiNation (SMASHINg) using both synthetic and real images. Furthermore, we show the application of our method to a range of image-based editing tasks on real images.Comment: project page: http://homes.esat.kuleuven.be/~krematas/DRM

    Lightness, Brightness, and Transparency in Optical See-Through Augmented Reality

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    Augmented reality (AR), as a key component of the future metaverse, has leaped from the research labs to the consumer and enterprise markets. AR optical see-through (OST) devices utilize transparent optical combiners to provide visibility of the real environment as well as superimpose virtual content on top of it. OST displays distinct from existing media because of their optical additivity, meaning the light reaching the eyes is composed of both virtual content and real background. The composition results in the intended virtual colors being distorted and perceived transparent. When the luminance of the virtual content decreases, the perceived lightness and brightness decrease, and the perceived transparency increases. Lightness, brightness, and transparency are modulated by one physical dimension (luminance), and all interact with the background and each other. In this research, we aim to identify and quantify the three perceptual dimensions, as well as build mathematical models to predict them. In the first part of the study, we focused on the perceived brightness and lightness with two experiments: a brightness partition scaling experiment to build brightness scales, and a diffuse white adjustment experiment to determine the absolute luminance level required for diffuse white appearances on 2D and 3D AR stimuli. The second part of the research targeted at the perceived transparency in the AR environment with three experiments. The transparency was modulated by the background Michelson contrast reduction in either average luminance or peak-to-peak luminance difference to investigate, and later illustrated, the fundamental mechanism evoking transparency perception. The first experiment measured the transparency detection thresholds and confirmed that contrast sensitivity functions with contrast adaptation could model the thresholds. Subsequently, the transparency perception was investigated through direct anchored scaling experiment by building perceived transparency scales from the virtual content contrast ratio to the background. A contrast-ratio-based model was proposed predicting the perceived transparency scales. Finally, the transparency equivalency experiment between the two types of contrast modulation confirmed the mechanism difference and validated the proposed model

    Brightness matching in optical see-through augmented reality

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    A visual experiment using a beam-splitter-based optical see-through augmented reality (OST-AR) setup tested the effect of the size and alignment of AR overlays with a brightness-matching task using physical cubes. Results indicate that more luminance is required whenARoverlays are oversized with respect to the cubes, showing that observers discount theARoverlay to a greater extent when it is more obviously a transparent layer. This is not explained by conventional color appearance modeling but supports an AR-specific model based on foreground-background discounting. The findings and model will help determine parameters for creating convincingARmanipulation of realworld objects

    Educational illustration of the historical city, education citizenship, and sustainable heritage

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    The Sustainable Development Goals identified by the United Nations (2030 agenda) aim to promote sustainable cities, the need to safeguard cultural heritage, and the importance of quality education. Through different projects, the DIDPATRI research group at the University of Barcelona has developed didactic iconographic models on the historical and heritage dimension of cities. Comprehensible proposals have been made by developing unique techniques and using easily accessible technologies. The working hypothesis has focused on the idea that the models of didactic iconography promote the understanding of the history of the city, and this enables educational actions and contributes to the formation of quality citizenship, aware of the importance of heritage, with a view to the sustainability of urban environments themselves. The components and the layout of the iconographic prototypes tested have been developed with the available technological variables, but, above all, they focus on the conceptual organization of the iconographic contents to show. In other words, it places greater emphasis on techniques than on subsidiary technologies for change. The development of different projects has generated models of empirical effectiveness, which methodologically have contributed to improving, in the key of sustainability, the knowledge of historical urban environments and respect for heritage. The case studies considered in this work are two of the most emblematic developed by the DIDPATRI group: the archaeological site of El Born in Barcelona, and the medieval site of La Seu de Urgell, in the Catalan Pyrenees

    Modeling Color Appearance in Augmented Reality

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    Augmented reality (AR) is a developing technology that is expected to become the next interface between humans and computers. One of the most common designs of AR devices is the optical see-through head- mounted display (HMD). In this design, the virtual content presented on the displays embedded inside the device gets optically superimposed on the real world which results in the virtual content being transparent. Color appearance in see-through designs of AR is a complicated subject, because it depends on many factors including the ambient light, the color appearance of the virtual content and color appearance of the real background. Similar to display technology, it is vital to control the color appearance of content for many applications of AR. In this research, color appearance in the see-through design of augmented reality environment is studied and modeled. Using a bench-top optical mixing apparatus as an AR simulator, objective measurements of mixed colors in AR were performed to study the light behavior in AR environment. Psychophysical color matching experiments were performed to understand color perception in AR. These experiments were performed first for simple 2D stimuli with single color both as background and foreground and later for more visually complex stimuli to better represent real content that is presented in AR. Color perception in AR environment was compared to color perception on a display which showed they are different from each other. The applicability of the CAM16 color appearance model, one of the most comprehensive current color appearance models, in AR environment was evaluated. The results showed that the CAM16 is not accurate in predicting the color appearance in AR environment. In order to model color appearance in AR environment, four approaches were developed using modifications in tristimulus and color appearance spaces, and the best performance was found to be for Approach 2 which was based on predicting the tristimulus values of the mixed content from the background and foreground color

    Spatial Augmented Reality Using Structured Light Illumination

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    Spatial augmented reality is a particular kind of augmented reality technique that uses projector to blend the real objects with virtual contents. Coincidentally, as a means of 3D shape measurement, structured light illumination makes use of projector as part of its system as well. It uses the projector to generate important clues to establish the correspondence between the 2D image coordinate system and the 3D world coordinate system. So it is appealing to build a system that can carry out the functionalities of both spatial augmented reality and structured light illumination. In this dissertation, we present all the hardware platforms we developed and their related applications in spatial augmented reality and structured light illumination. Firstly, it is a dual-projector structured light 3D scanning system that has two synchronized projectors operate simultaneously, consequently it outperforms the traditional structured light 3D scanning system which only include one projector in terms of the quality of 3D reconstructions. Secondly, we introduce a modified dual-projector structured light 3D scanning system aiming at detecting and solving the multi-path interference. Thirdly, we propose an augmented reality face paint system which detects human face in a scene and paints the face with any favorite colors by projection. Additionally, the system incorporates a second camera to realize the 3D space position tracking by exploiting the principle of structured light illumination. At last, a structured light 3D scanning system with its own built-in machine vision camera is presented as the future work. So far the standalone camera has been completed from the a bare CMOS sensor. With this customized camera, we can achieve high dynamic range imaging and better synchronization between the camera and projector. But the full-blown system that includes HDMI transmitter, structured light pattern generator and synchronization logic has yet to be done due to the lack of a well designed high speed PCB

    Roadmap on digital holography [Invited]

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    This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography

    Electronic Imaging & the Visual Arts. EVA 2019 Florence

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    The Publication is following the yearly Editions of EVA FLORENCE. The State of Art is presented regarding the Application of Technologies (in particular of digital type) to Cultural Heritage. The more recent results of the Researches in the considered Area are presented. Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; New Science and Culture Developments & Applications; New Technical Developments & Applications; Cultural Activities – Real and Virtual Galleries and Related Initiatives, Access to the Culture Information. One Workshop regards Innovation and Enterprise. The more recent results of the Researches at national and international level are reported in the Area of Technologies and Culture Heritage, also with experimental demonstrations of developed Activities
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