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Item MTV-Player: Interactive Spatio-Temporal Exploration of Compressed Large-Scale Time-Varying Rectilinar Scalar Volumes(The Eurographics Association, 2019) DÃaz, Jose; Marton, Fabio; Gobbetti, Enrico; Agus, Marco and Corsini, Massimiliano and Pintus, RuggeroWe present an approach for supporting fully interactive exploration of massive time-varying rectilinear scalar volumes on commodity platforms. We decompose each frame into a forest of bricked octrees. Each brick is further subdivided into smaller blocks, which are compactly approximated by quantized variable-length sparse linear combinations of prototype blocks stored in a data-dependent dictionary learned from the input sequence. This variable bit-rate compact representation, obtained through a tolerance-driven learning and approximation process, is stored in a GPU-friendly format that supports direct adaptive streaming to the GPU with spatial and temporal random access. An adaptive compression-domain renderer closely coordinates off-line data selection, streaming, decompression, and rendering. The resulting system provides total control over the spatial and temporal dimensions of the data, supporting the same exploration metaphor as traditional video players. Since we employ a highly compressed representation, the bandwidth provided by current commodity platforms proves sufficient to fully stream and render dynamic representations without relying on partial updates, thus avoiding any unwanted dynamic effects introduced by current incremental loading approaches. Moreover, our variable-rate encoding based on sparse representations provides high-quality approximations, while offering real-time decoding and rendering performance. The quality and performance of our approach is demonstrated on massive time-varying datasets at the terascale, which are nonlinearly explored at interactive rates on a commodity graphics PC.Item Aging Prediction of Cultural Heritage Samples Based on Surface Microgeometry(The Eurographics Association, 2018) Ciortan, Irina Mihaela; Marchioro, Giacomo; Daffara, Claudia; Pintus, Ruggero; Gobbetti, Enrico; Giachetti, Andrea; Sablatnig, Robert and Wimmer, MichaelA critical and challenging aspect for the study of Cultural Heritage (CH) assets is related to the characterization of the materials that compose them and to the variation of these materials with time. In this paper, we exploit a realistic dataset of artificially aged metallic samples treated with different coatings commonly used for artworks' protection in order to evaluate different approaches to extract material features from high-resolution depth maps. In particular, we estimated, on microprofilometric surface acquisitions of the samples, performed at different aging steps, standard roughness descriptors used in materials science as well as classical and recent image texture descriptors. We analyzed the ability of the features to discriminate different aging steps and performed supervised classification tests showing the feasibility of a texture-based aging analysis and the effectiveness of coatings in reducing the surfaces' change with time.Item Objective and Subjective Evaluation of Virtual Relighting from Reflectance Transformation Imaging Data(The Eurographics Association, 2018) Pintus, Ruggero; Dulecha, Tinsae; Jaspe, Alberto; Giachetti, Andrea; Ciortan, Irina; Gobbetti, Enrico; Sablatnig, Robert and Wimmer, MichaelReflectance Transformation Imaging (RTI) is widely used to produce relightable models from multi-light image collections. These models are used for a variety of tasks in the Cultural Heritage field. In this work, we carry out an objective and subjective evaluation of RTI data visualization. We start from the acquisition of a series of objects with different geometry and appearance characteristics using a common dome-based configuration. We then transform the acquired data into relightable representations using different approaches: PTM, HSH, and RBF. We then perform an objective error estimation by comparing ground truth images with relighted ones in a leave-one-out framework using PSNR and SSIM error metrics. Moreover, we carry out a subjective investigation through perceptual experiments involving end users with a variety of backgrounds. Objective and subjective tests are shown to behave consistently, and significant differences are found between the various methods. While the proposed analysis has been performed on three common and state-of-the-art RTI visualization methods, our approach is general enough to be extended and applied in the future to new developed multi-light processing pipelines and rendering solutions, to assess their numerical precision and accuracy, and their perceptual visual quality.Item Web-based Multi-layered Exploration of Annotated Image-based Shape and Material Models(The Eurographics Association, 2019) Villanueva, Alberto Jaspe; Pintus, Ruggero; Giachetti, Andrea; Gobbetti, Enrico; Rizvic, Selma and Rodriguez Echavarria, KarinaWe introduce a novel versatile approach for letting users explore detailed image-based shape and material models integrated with structured, spatially-associated descriptive information. We represent the objects of interest as a series of registered layers of image-based shape and material information. These layers are represented at multiple scales, and can come out of a variety of pipelines and include both RTI representations and spatially-varying normal and BRDF fields, eventually as a result of fusing multi-spectral data. An overlay image pyramid associates visual annotations to the various scales. The overlay pyramid of each layer can be easily authored at data preparation time using widely available image editing tools. At run-time, an annotated multi-layered dataset is made available to clients by a standard web server. Users can explore these datasets on a variety of devices, from mobile phones to large scale displays in museum installations, using JavaScript/WebGL2 clients capable to perform layer selection, interactive relighting and enhanced visualization, annotation display, and focus-and-context multiple-layer exploration using a lens metaphor. The capabilities of our approach are demonstrated on a variety of cultural heritage use cases involving different kinds of annotated surface and material models.Item Interactive Volumetric Visual Analysis of Glycogen-derived Energy Absorption in Nanometric Brain Structures(The Eurographics Association and John Wiley & Sons Ltd., 2019) Agus, Marco; Calì, Corrado; Al-Awami, Ali K.; Gobbetti, Enrico; Magistretti, Pierre J.; Hadwiger, Markus; Gleicher, Michael and Viola, Ivan and Leitte, HeikeDigital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis tools targeted to develop and test hypotheses of brain development and activity. In this work, we focus on neuroenergetics, a field where neuroscientists analyze nanoscale brain morphology and relate energy consumption to glucose storage in form of glycogen granules. In order to facilitate the understanding of neuroenergetic mechanisms, we propose a novel customized pipeline for the visual analysis of nanometric-level reconstructions based on electron microscopy image data. Our framework supports analysis tasks by combining i) a scalable volume visualization architecture able to selectively render image stacks and corresponding labelled data, ii) a method for highlighting distance-based energy absorption probabilities in form of glow maps, and iii) a hybrid connectivitybased and absorption-based interactive layout representation able to support queries for selective analysis of areas of interest and potential activity within the segmented datasets. This working pipeline is currently used in a variety of studies in the neuroenergetics domain. Here, we discuss a test case in which the framework was successfully used by domain scientists for the analysis of aging effects on glycogen metabolism, extracting knowledge from a series of nanoscale brain stacks of rodents somatosensory cortex.Item State-of-the-art in Multi-Light Image Collections for Surface Visualization and Analysis(The Eurographics Association and John Wiley & Sons Ltd., 2019) Pintus, Ruggero; Dulecha, Tinsae Gebrechristos; Ciortan, Irina Mihaela; Gobbetti, Enrico; Giachetti, Andrea; Laramee, Robert S. and Oeltze, Steffen and Sedlmair, MichaelMulti-Light Image Collections (MLICs), i.e., stacks of photos of a scene acquired with a fixed viewpoint and a varying surface illumination, provide large amounts of visual and geometric information. In this survey, we provide an up-to-date integrative view of MLICs as a mean to gain insight on objects through the analysis and visualization of the acquired data. After a general overview of MLICs capturing and storage, we focus on the main approaches to produce representations usable for visualization and analysis. In this context, we first discuss methods for direct exploration of the raw data. We then summarize approaches that strive to emphasize shape and material details by fusing all acquisitions in a single enhanced image. Subsequently, we focus on approaches that produce relightable images through intermediate representations. This can be done both by fitting various analytic forms of the light transform function, or by locally estimating the parameters of physically plausible models of shape and reflectance and using them for visualization and analysis. We finally review techniques that improve object understanding by using illustrative approaches to enhance relightable models, or by extracting features and derived maps. We also review how these methods are applied in several, main application domains, and what are the available tools to perform MLIC visualization and analysis. We finally point out relevant research issues, analyze research trends, and offer guidelines for practical applications.Item A Framework for GPU-accelerated Exploration of Massive Time-varying Rectilinear Scalar Volumes(The Eurographics Association and John Wiley & Sons Ltd., 2019) Marton, Fabio; Agus, Marco; Gobbetti, Enrico; Gleicher, Michael and Viola, Ivan and Leitte, HeikeWe introduce a novel flexible approach to spatiotemporal exploration of rectilinear scalar volumes. Our out-of-core representation, based on per-frame levels of hierarchically tiled non-redundant 3D grids, efficiently supports spatiotemporal random access and streaming to the GPU in compressed formats. A novel low-bitrate codec able to store into fixed-size pages a variable-rate approximation based on sparse coding with learned dictionaries is exploited to meet stringent bandwidth constraint during time-critical operations, while a near-lossless representation is employed to support high-quality static frame rendering. A flexible high-speed GPU decoder and raycasting framework mixes and matches GPU kernels performing parallel object-space and image-space operations for seamless support, on fat and thin clients, of different exploration use cases, including animation and temporal browsing, dynamic exploration of single frames, and high-quality snapshots generated from near-lossless data. The quality and performance of our approach are demonstrated on large data sets with thousands of multi-billion-voxel frames.Item Crack Detection in Single- and Multi-Light Images of Painted Surfaces using Convolutional Neural Networks(The Eurographics Association, 2019) Dulecha, Tinsae Gebrechristos; Giachetti, Andrea; Pintus, Ruggero; Ciortan, Irina; Villanueva, Alberto Jaspe; Gobbetti, Enrico; Rizvic, Selma and Rodriguez Echavarria, KarinaCracks represent an imminent danger for painted surfaces that needs to be alerted before degenerating into more severe aging effects, such as color loss. Automatic detection of cracks from painted surfaces' images would be therefore extremely useful for art conservators; however, classical image processing solutions are not effective to detect them, distinguish them from other lines or surface characteristics. A possible solution to improve the quality of crack detection exploits Multi-Light Image Collections (MLIC), that are often acquired in the Cultural Heritage domain thanks to the diffusion of the Reflectance Transformation Imaging (RTI) technique, allowing a low cost and rich digitization of artworks' surfaces. In this paper, we propose a pipeline for the detection of crack on egg-tempera paintings from multi-light image acquisitions and that can be used as well on single images. The method is based on single or multi-light edge detection and on a custom Convolutional Neural Network able to classify image patches around edge points as crack or non-crack, trained on RTI data. The pipeline is able to classify regions with cracks with good accuracy when applied on MLIC. Used on single images, it can give still reasonable results. The analysis of the performances for different lighting directions also reveals optimal lighting directions.Item Recovering 3D Indoor Floor Plans by Exploiting Low-cost Spherical Photography(The Eurographics Association, 2018) Pintore, Giovanni; Ganovelli, Fabio; Pintus, Ruggero; Scopigno, Roberto; Gobbetti, Enrico; Fu, Hongbo and Ghosh, Abhijeet and Kopf, JohannesWe present a novel approach to automatically recover, from a small set of partially overlapping panoramic images, an indoor structure representation in terms of a 3D floor plan registered with a set of 3D environment maps. Our improvements over previous approaches include a new method for geometric context extraction based on a 3D facets representation, which combines color distribution analysis of individual images with sparse multi-view clues, as well as an efficient method to combine the facets from different point-of-view in the same world space, considering the reliability of the facets contribution. The resulting capture and reconstruction pipeline automatically generates 3D multi-room environments where most of the other previous approaches fail, such as in presence of hidden corners, large clutter and sloped ceilings, even without involving additional dense 3D data or tools. We demonstrate the effectiveness and performance of our approach on different real-world indoor scenes.Item Automatic Modeling of Cluttered Multi-room Floor Plans From Panoramic Images(The Eurographics Association and John Wiley & Sons Ltd., 2019) Pintore, Giovanni; Ganovelli, Fabio; Villanueva, Alberto Jaspe; Gobbetti, Enrico; Lee, Jehee and Theobalt, Christian and Wetzstein, GordonWe present a novel and light-weight approach to capture and reconstruct structured 3D models of multi-room floor plans. Starting from a small set of registered panoramic images, we automatically generate a 3D layout of the rooms and of all the main objects inside. Such a 3D layout is directly suitable for use in a number of real-world applications, such as guidance, location, routing, or content creation for security and energy management. Our novel pipeline introduces several contributions to indoor reconstruction from purely visual data. In particular, we automatically partition panoramic images in a connectivity graph, according to the visual layout of the rooms, and exploit this graph to support object recovery and rooms boundaries extraction. Moreover, we introduce a plane-sweeping approach to jointly reason about the content of multiple images and solve the problem of object inference in a top-down 2D domain. Finally, we combine these methods in a fully automated pipeline for creating a structured 3D model of a multi-room floor plan and of the location and extent of clutter objects. These contribution make our pipeline able to handle cluttered scenes with complex geometry that are challenging to existing techniques. The effectiveness and performance of our approach is evaluated on both real-world and synthetic models.