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Item A 3 Cent Recognizer: Simple and Effective Retrieval and Classification of Mid-air Gestures from Single 3D Traces(The Eurographics Association, 2017) Caputo, Fabio Marco; Prebianca, Pietro; Carcangiu, Alessandro; Spano, Lucio D.; Giachetti, Andrea; Andrea Giachetti and Paolo Pingi and Filippo StancoIn this paper we present a simple 3D gesture recognizer based on trajectory matching, showing its good performances in classification and retrieval of command gestures based on single hand trajectories. We demonstrate that further simplifications in porting the classic "1 dollar" algorithm approach from the 2D to the 3D gesture recognition and retrieval problems can result in very high classification accuracy and retrieval scores even on datasets with a large number of different gestures executed by different users. Furthermore, recognition can be good even with heavily subsampled path traces and with incomplete gestures.Item STRONGER: Simple TRajectory-based ONline GEsture Recognizer(The Eurographics Association, 2021) Emporio, Marco; Caputo, Ariel; Giachetti, Andrea; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà , EmanueleIn this paper, we present STRONGER, a client-server solution for the online gesture recognition from captured hands' joints sequences. The system leverages a CNN-based recognizer improving current state-of-the-art solutions for segmented gestures classification, trained and tested for the online gesture recognition task on a recent benchmark including heterogeneous gestures. The recognizer provides good classification accuracy and a limited number of false positives on most of the gesture classes of the benchmark used and has been used to create a demo application in a Mixed Reality scenario using an Hololens 2 optical see through Head-Mounted Display with hand tracking capability.Item TESTIMAGES: a Large-scale Archive for Testing Visual Devices and Basic Image Processing Algorithms(The Eurographics Association, 2014) Asuni, Nicola; Giachetti, Andrea; Andrea GiachettiWe present the TESTIMAGES archive, a huge and free collection of sample images designed for analysis and quality assessment of different kinds of displays (i.e. monitors, televisions and digital cinema projectors) and image processing tecnhiques. The archive includes more than 2 million images originally acquired and divided in four different categories: SAMPLING and SAMPLING_PATTERNS (aimed at testing resampling algorithms), COLOR (aimed at testing color rendering on different displays) and PATTERNS (aimed at testing the rendering of standard geometrical patterns). The archive is currently online as a SourceForge project and, even if not yet publicized in the scientific community, it has already been used in different contexts and cited in scientific publications. We plan to extend the archive including datasets for other kinds of specific analyses.Item Smart Tools and Applications in computer Graphics - Eurographics Italian Chapter Conference 2017: Frontmatter(Eurographics Association, 2017) Giachetti, Andrea; Pingi, Paolo; Stanco, Filippo; Andrea Giachetti and Paolo Pingi and Filippo StancoItem A Practical Vision Based Approach to Unencumbered Direct Spatial Manipulation in Virtual Worlds(The Eurographics Association, 2007) Bettio, Fabio; Giachetti, Andrea; Gobbetti, Enrico; Marton, Fabio; Pintore, Giovanni; Raffaele De Amicis and Giuseppe ContiWe present a practical approach for developing interactive environments that allows humans to interact with large complex 3D models without them having to manually operate input devices. The system provides support for scene manipulation based on hand tracking and gesture recognition and for direct 3D interaction with the 3D models in the display space if a suitably registered 3D display is used. Being based on markerless tracking of a user's two hands, the system does not require users to wear any input or output devices. 6DOF input is provided by using both hands simultaneously,making the tracker more robust since only tracking of position information is required. The effectiveness of the method is demonstrated with a simple application for model manipulation on a large stereo display, in which rendering constraints are met by employing state-of-the-art multiresolution techniques.Item Towards Advanced Volumetric Display of the Human Musculoskeletal System(The Eurographics Association, 2008) Agus, Marco; Giachetti, Andrea; Gobbetti, Enrico; Guitián, José Antonio Iglesias; Marton, Fabio; Vittorio Scarano and Rosario De Chiara and Ugo ErraWe report on our research results on effective volume visualization techniques for medical and anatomical data. Our volume rendering approach employs GPU accelerated out-of-core direct rendering algorithms to fully support high resolution, 16 bits, raw medical datasets as well as segmentation. Images can be presented on a special light field display based on projection technology. Human anatomical data appear to moving viewers floating in the light field display space and can be interactively manipulated.Item Edge Adaptive and Energy Preserving Volume Upscaling for High Quality Volume Rendering(The Eurographics Association, 2010) Giachetti, Andrea; Guitián, J. A. Iglesias; Gobbetti, Enrico; Enrico Puppo and Andrea Brogni and Leila De FlorianiWe describe an edge-directed optimization-based method for volumetric data supersampling. The method is based on voxel splitting and iterative refinement performed with a greedy optimization driven by the smoothing of second order gray level derivatives and the assumption that the average gray level in the original voxels region cannot change. Due to these assumptions, the method, which is the 3D extension of a recently proposed technique, is particularly suitable for upscaling medical imaging data creating physically reasonable voxel values and overcoming the so-called partial volume effect. The good quality of the results obtained is demonstrated through experimental tests. Furthermore, we show how offline 3D upscaling of volumes can be coupled with recent techniques to perform high quality volume rendering of large datasets, obtaining a better inspection of medical volumetric dataItem Approximating Shapes with Standard and Custom 3D Printed LEGO Bricks(The Eurographics Association, 2021) Fanni, Filippo Andrea; Dal Bello, Alberto; Sbardellini, Simone; Giachetti, Andrea; Frosini, Patrizio and Giorgi, Daniela and Melzi, Simone and Rodolà , EmanueleIn this paper, we present a work-in-progress aimed at developing a pipeline for the fabrication of shapes reproducing digital models with a combination of standard LEGO bricks and 3D printed custom elements. The pipeline starts searching for the ideal alignment of the 3D model with the brick grid. It then employs a novel approach for shape "legolization" using a outside-in heuristic to limit critical configuration, and separates an external shell and an internal part. Finally, it exploits shape booleans to create the external custom parts to be 3D printed.Item 3-SHIRT: Three-Dimensional Shape Indexing and Retrieval Techniques(The Eurographics Association, 2008) Castellani, Umberto; Cortelazzo, Guido Maria; Cristani, M.; Delponte, Elisabetta; Fusiello, Andrea; Giachetti, Andrea; Mizzaro, Stefano; Odone, Francesca; Puppo, Enrico; Scateni, Riccardo; Zanuttigh, Pietro; Vittorio Scarano and Rosario De Chiara and Ugo ErraThis paper describes the work that has been done during the first year of the 3-SHIRT project, which aims at developing innovative solutions in all the phases of content-based 3D shape retrieval, namely: shape analysis and segmentation, design of shape descriptors, shape indexing and matching, and evaluation.Item Practical Free-form RTI Acquisition with Local Spot Lights(The Eurographics Association, 2016) Pintus, Ruggero; Ciortan, Irina Mihaela; Giachetti, Andrea; Gobbetti, Enrico; Giovanni Pintore and Filippo StancoWe present an automated light calibration pipeline for free-form acquisition of shape and reflectance of objects using common off-the-shelf illuminators, such as LED lights, that can be placed arbitrarily close to the objects. We acquire multiple digital photographs of the studied object shot from a stationary camera. In each photograph, a light is freely positioned around the object in order to cover a wide variety of illumination directions. While common free-form acquisition approaches are based on the simplifying assumptions that the light sources are either sufficiently far from the object that all incoming light can be modeled using parallel rays, or that lights are local points emitting uniformly in space, we use the more realistic model of a scene lit by a moving local spot light with exponential fall-off depending on the cosine of the angle between the spot light optical axis and the illumination direction, raised to the power of the spot exponent. We recover all spot light parameters using a multipass numerical method. First, light positions are determined using standard methods used in photometric stereo approaches. Then, we exploit measures taken on a Lambertian reference planar object to recover the spot light exponent and the per-image spot light optical axis; we minimize the difference between the observed reflectance and the reflectance synthesized by using the near-field Lambertian equation. The optimization is performed in two passes, first generating a starting solution and then refining it using a Levenberg-Marquardt iterative minimizer. We demonstrate the effectiveness of the method based on an error analysis performed on analytical datasets, as well as on real-world experiments.