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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 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 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.