Italian Chapter Conference 2015 - Smart Tools and Apps in computer Graphics

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https://diglib7.eg.org/handle/10.2312/13813

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    Automatic GPU-based Algorithm for OMERACT-RAMRIS Score Quantification in Rheumatoid Arthritis
    (The Eurographics Association, 2015) Cesario, Lorenzo; Parascandolo, Patrizia; Vosilla, Loris; Troglio, Giulia; Viano, Gianni; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    Rheumatoid Arthritis (RA) is a systemic disease that affects the synovial joints. Currently, the gold standard measurement for tracking the progression of the disease involves a semi-quantitative assessment of bone erosion, bone marrow edema, and synovitis in Magnetic Resonance Images. The Outcome Measures in Rheumatology Clinical Trials (OMERACT) Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS) system represents a useful standard for the assessment of RA. However, the use of RAMRIS system is time-consuming and tedious and requires a long learning curve. The work presented in this paper is aimed at identifying how computer automation, using parallel computing on the Graphics Processing Unit (GPU), can be used to quantify OMERACT-RAMRIS score. The proposed algorithm is fully integrated in a Computer Aided Diagnosis (CAD) system named RheumaSCORE (Softeco Sismat Srl) and enables users-even non-expert ones-to evaluate bone erosion in a short time and with little training. Preliminary results of qualitative and quantitative validation are presented and discussed at the end of the paper.
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    Distributed Processing of Large Polygon Meshes
    (The Eurographics Association, 2015) Cabiddu, Daniela; Attene, Marco; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    A system is described to remotely perform complex geometry processing on arbitrarily large triangle meshes. A distributed network of servers provides both the software and hardware necessary to undertake the computations, while the overall execution is managed by a central engine that both invokes appropriate Web services and handles the data transmission. Nothing more than a standard web browser needs to be installed on the client machine hosting the input mesh. The user interface allows to build complex pipelines by stacking geometric algorithms and by controlling their execution through conditions and cycles. Besides the technological contribution, an innovative mesh transfer protocol is described to treat large datasets whose transmission across scattered servers may represent a bottleneck. Also, efficiency and effectiveness are guaranteed thanks to a novel divide and conquer approach that the engine exploits to partition large meshes into smaller pieces, each delivered to a dedicated server for parallel processing. Based on this paradigm, a distributed simplification algorithm has been implemented which proves that the overhead due to data transmission is negligible, as it is much lower than the gain in speed provided by parallel processing.
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    Exploiting Silhouette Descriptors and Synthetic Data for Hand Gesture Recognition
    (The Eurographics Association, 2015) Memo, Alvise; Minto, Ludovico; Zanuttigh, Pietro; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    This paper proposes a novel real-time hand gesture recognition scheme explicitly targeted to depth data. The hand silhouette is firstly extracted from the acquired data and then two ad-hoc feature sets are computed from this representation. The first is based on the local curvature of the hand contour, while the second represents the thickness of the hand region close to each contour point using a distance transform. The two feature sets are rearranged in a three dimensional data structure representing the values of the two features at each contour location and then this representation is fed into a multi-class Support Vector Machine. The classifier is trained on a synthetic dataset generated with an ad-hoc rendering system developed for the purposes of this work. This approach allows a fast construction of the training set without the need of manually acquiring large training datasets. Experimental results on real data show how the approach is able to achieve a 90% accuracy on a typical hand gesture recognition dataset with very limited computational resources.
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    Faster Ray-Traced Shadows for Hybrid Rendering of Fully Dynamic Scenes by Pre-BVH Culling
    (The Eurographics Association, 2015) Selgrad, Kai; Müller, Jonas; Stamminger, Marc; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    With ever increasing ray traversal and hierarchy construction performance the application of ray tracing to problems often tackled by rasterization-based algorithms is becoming a viable alternative. This is especially desirable as the ground truth for these algorithms is often determined by using ray tracing and thus directly applying it is the simplest way to generate images satisfying the reference. In this paper we propose a very efficient pre-process to speed up the construction and traversal of sub-optimal, but fast-to-build hierarchies used for interactive ray tracing and show how it can be applied to shadow rays in a hybrid environment, where ray tracing is used to sample area lights for scene positions found and shaded via rasterization.
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    Frontmatter: Smart Tools and Applications in computer Graphics (STAG)
    (The Eurographics Association, 2015) Giachetti, Andrea; Biasotti, Silvia; Tarini, Marco; Andrea Giachetti and Silvia Biasotti and Marco Tarini
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    Grontocrawler: Graph-Based Ontology Exploration
    (The Eurographics Association, 2015) Agibetov, Asan; Patanè, Giuseppe; Spagnuolo, Michela; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    Biomedical ontologies helps discover hidden semantic links between heterogeneous and multi-scale biomedical datasets. Computational methods to ontology analysis may provide a semantic flavor to data analysis of biomedical mathematical models and help discover hidden links. In this paper we present Grontocrawler - a framework for visual ontology exploration applied to the biomedical domain. We define an OWL sublanguage - L and we present a methodology for transformation of L ontologies into directed labelled graphs. We then show how Social Network Analysis techniques (e.g., centrality measures, graph partitioning, community detection) can be used to i) filter the information presented to the user, and ii) provide a summary of knowledge encoded in the ontology. Finally, we show the application of ontology exploration in the biomedical domain to help discover hidden links between the biomedical datasets.
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    HIJSON: Cartographic Document for Web Modeling of Interactive Indoor Mapping
    (The Eurographics Association, 2015) Spini, Federico; Sportillo, Marco; Virgadamo, Marco; Marino, Enrico; Bottaro, Antonio; Paoluzzi, Alberto; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    This paper introduces HIJSON, a novel indoor cartographic document format with several enhancements. The document is generated using LAR (Linear Algebraic Representation), so allowing for cellular complexes with general topology and shape. A software framework FIVE is also presented, that relies on HIJSON documents and is entirely based on web technologies. With respect to current cartographic formats, HIJSON suggests four major enhancements: (a) exposes a hierarchical structure; (b) uses local metric coordinate systems; (c) may import external geometric models; (d) accepts semantic extensions. The semantic extensions supported by the FIVE framework architecture encapsulate the details about communication protocols, rendering style, and exchanged and displayed information, allowing the HIJSON format to be extended with any sort of models of objects, sensors or behaviors.
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    Low-cost Experimental Setups for Mid-air 3D Reconstruction
    (The Eurographics Association, 2015) Dancu, Alexandru; Fratarcangeli, Marco; Fourgeaud, Mickaël; Franjcic, Zlatko; Chindea, Daniel; Fjeld, Morten; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    The reconstruction of the physical environment using a depth sensor involves data-intensive computations which are difficult to implement on mobile systems (e.g., tracking and aligning the position of the sensor with the depth maps). In this paper, we present two practical experimental setups for scanning and reconstructing real objects employing low-price, off-the-shelf embedded components and open-source libraries. As a test case, we scan and reconstruct a 23 m high statue using an octocopter without employing external hardware
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    Mobile Multiview Diffuse Texture Extraction
    (The Eurographics Association, 2015) Kán, Peter; Kaufmann, Hannes; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    This paper presents a novel method for diffuse texture extraction from a set of multiview images. We address the problem of specularities removal by pixel value minimization across multiple automatically aligned input images. Our method is based on the fact that the presence of specular reflection only increases the captured pixel value. Moreover, we propose an algorithm for estimation of material region in the image by optimization on the GPU. Previous methods for diffuse component separation from multiple images require a complex hardware setup. In contrast to that, our method is highly usable because only a mobile phone is needed to reconstruct diffuse texture in an environment with arbitrary lighting. Moreover, our method is fully automatic and besides capturing of images from multiple viewpoints it does not require any user intervention. Many fields can benefit from our method, particularly material reconstruction, image processing, and digital content creation.
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    Practical Medial Axis Filtering for Occlusion-Aware Contours
    (The Eurographics Association, 2015) Livesu, Marco; Scateni, Riccardo; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    We propose a filtering system for occlusion-aware contours. Given a point of view, we use the silhouette of a 3D shape from that point of view, its medial axis and a map of the occluded areas. Our filter is able to select the points of the medial axis which are projections of the curve-skeleton of the 3D shape, discarding all the points affected by occlusions. Our algorithm is easy to implement and works in real time. It can be plugged as is into existing methods for curve-skeleton extraction from 2D images; it can be used to robustly rank silhouettes according to how much they are representative of the 3D shape that generated them and can also be used for shape recognition from images or video sequences.
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    RameshCleaner: Conservative Fixing of Triangular Meshes
    (The Eurographics Association, 2015) Centin, Marco; Signoroni, Alberto; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    In this work, after a careful examination of the most common errors and flaws which typically occur in meshes produced by 3D scanning processes, we propose a set of fixing tools which solve effectively several important mesh defects while preserving the original data. The proposed tools are then organized and activated in the RameshCleaner pipeline allowing the user to take advantage of a semi-automated fixing solution, optimized for speed and efficiency, as well as of the possibility to selectively activate individual tools. The comparison, over a set of representative scanned models, with free and commercial semi-automated fixing solutions gives a significant evidence of the defect abatement and computational speed characteristics of the proposed system.
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    Recovering Intrinsic Images by Minimizing Image Complexity
    (The Eurographics Association, 2015) Stefani, Nicola; Fusiello, Andrea; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    This paper tackles the problem of decomposing a single image into two intrinsic images - a shading image (the illumination at each point) and a reflectance image (the colour at each point). Assuming a linear response of the camera, the acquired image I(x; y) is modelled as the product of the shading S(x; y) and the reflectance R(x; y) (collectively called intrinsic images): the goal is to recover S and R from I(x; y). The proposed method stems from the observation that R is "simpler" than I, in some sense related to its information content. This allows to formulate the problem as the minimization over all the possible S of a cost function describing the complexity of a tentative reflectance image given a shading image S. Given a 3D model of the scene, the orientation of the camera, and an illumination model, S can be parameterized with the position of light sources on a hemisphere. Preliminary experiments in a simulated environment validate the substance of the method, although many details will be subject of further improvement.
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    RiftArt: Bringing Masterpieces in the Classroom through Immersive Virtual Reality
    (The Eurographics Association, 2015) Casu, Andrea; Spano, Lucio Davide; Sorrentino, Fabio; Scateni, Riccardo; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    The recent development in consumer hardware lowers the cost barrier for adopting immersive Virtual Reality (VR) solutions, which could be an option for classroom use in the near future. In this paper, we introduce RiftArt, a VR tool for supporting the teaching and studying of Art History. Using RiftArt the teachers can configure virtual museum rooms, with artwork models inside, and enhance them with multimodal annotation. The environment supports both the teachers during the lesson and the students during rehearsal. The application, implemented completely using Web technologies, can be visualized on large screens and head mounted displays. The user test results advance the understanding of the VR effects on classroom usage. We demonstrate that VR increases the motivation of high-school students towards studying Art History and we provide an in-depth analysis of the factors that contribute to this result.
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    Robust 3D Pose Estimation of a Laparoscopic Instrument with three Landmarks
    (The Eurographics Association, 2015) Carletti, Marco; Zerbato, Davide; Dall'Alba, Diego; Calanca, Andrea; Fiorini, Paolo; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    Knowing surgeon movements during laparoscopic training may provide useful data to speed up the learning process by means of instantaneous error correction and performance evaluation. The first step toward this knowledge is the identification of laparoscopic tool pose in the training environment. In this paper we propose a method to estimate in real time the 3D pose of laparoscopic instruments using a standard camera and three non invasive colored markers applied on the tool stem. The proposed method takes advantage of closed form solution for the problem which speeds up the computation and improves the precision and accuracy of the results. In addition the method handles occlusions even without any marker tracking algorithm thanks to the automatic identification of the insertion point. The method is evaluated in terms of precision, accuracy and real time execution. Results show that it can be effectively used in common training scenarios.
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    Scene Segmentation Based on NURBS Surface Fitting Metrics
    (The Eurographics Association, 2015) Pagnutti, Giampaolo; Zanuttigh, Pietro; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    This paper proposes a segmentation scheme jointly exploiting color and depth data within a recursive region splitting framework. A set of multi-dimensional vectors is built from color and depth data and the scene is segmented in two parts using normalized cuts spectral clustering. Then a NURBS model is fitted on each of the two parts and various metrics based on the surface fitting results are used to measure the plausibility that each segment represents a single surface or object. Segments that do not represent a single surface are recursively split in a tree-structured procedure until the final segmentation is obtained. Different metrics based on the fitting error and on the curvature of the fitted surfaces are presented and tested inside this framework. Experimental results show how a reliable scene segmentation can be obtained from this procedure.
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    SemAnatomy3D: Annotation of Patient-Specific Anatomy
    (The Eurographics Association, 2015) Banerjee, Imon; Patanè, Giuseppe; Spagnuolo, Michela; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    In the digital age of medicine, patient-specific 3D anatomical reconstructions are becoming increasingly relevant in several applications, starting from bio-mechanical simulation, virtual surgery, implant design to computerassisted diagnosis. While problems related to imaging and 3D reconstruction have been largely resolved by the advancement in technologies, tools for extracting, coding, sharing and retrieving the semantic content of the patient-specific 3D models are still far from being satisfactory. In this context, we propose SemAnatomy3D framework that aims to bridge the semantic gap between patient-specific 3D geometry and formalized domain knowledge for making the semantics more usable for the definition of patient-specific atlas of anatomy. The purpose of this paper is to describe primary components of the framework. We specialized our framework for the carpal region, but, in principle, it can support similar tasks for other anatomical districts.
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    A Semi-automatic Algorithm for Applying the Ken Burns Effect
    (The Eurographics Association, 2015) Allegra, Dario; Stanco, Filippo; Valenti, Grigori; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    In historical documentaries, video material often is not available. For this reason they are mainly made by using static material such as old photographs. To make this material more endearing and dynamic an effect known as ''Ken Burns Effect'' can be applied to the static images. It consists in a mix of panning and zooming effect applied to different objects which belong to an image. Hence, considerable user experience with photo and video editing software is required to successfully separate the objects from the background and to animate them to produce a high quality result. In this paper, we present an algorithm to apply Ken Burns effect with a minimal user interaction. The proposed solution exploits Statistical Region Merging segmentation algorithm to support the user in the process of separation of the objects from the background. Moreover, Inpainting algorithms are employed to fill the empty regions which becomes visible when an object is moved from its original position. Finally a random video can be produced from different ''animated'' images.
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    Skeleton Lab: an Interactive Tool to Create, Edit, and Repair Curve-Skeletons
    (The Eurographics Association, 2015) Barbieri, Simone; Meloni, Pietro; Usai, Francesco; Scateni, Riccardo; Andrea Giachetti and Silvia Biasotti and Marco Tarini
    Curve-skeletons are well known shape descriptors, able to encode topological and structural information of a shape. The range of applications in which they are used comprises, to name a few, computer animation, shape matching, modelling and remeshing. Different tools for automatically extracting the curve-skeleton for a given input mesh are currently available, as well as inverse skeletonization tools, where a user-defined skeleton is taken as input in order to build a mesh that reflects the encoded structure. Although their use is broad, an automatically extracted curve-skeleton is usually not well-suited for the next pipeline step in which they will be used. We present a tool for creating, editing and repairing curve-skeletons whose aim is to allow users to obtain, within minutes, curve-skeletons that are tailored for their specific task.