Capturing and viewing gigapixel images

We present a system to capture and view "Gigapixel images": very high resolution, high dynamic range, and wide angle imagery consisting of several billion pixels each. A specialized camera mount, in combination with an automated pipeline for alignment, exposure compensation, and stitching, provide the means to acquire Gigapixel images with a standard camera and lens. More importantly, our novel viewer enables exploration of such images at interactive rates over a network, while dynamically and smoothly interpolating the projection between perspective and curved projections, and simultaneously modifying the tone-mapping to ensure an optimal view of the portion of the scene being viewed.publishe

Capturing and viewing gigapixel images

We present a system to capture and view "Gigapixel images": very high resolution, high dynamic range, and wide angle imagery consisting of several billion pixels each. A specialized camera mount, in combination with an automated pipeline for alignment, exposure compensation, and stitching, provide the means to acquire Gigapixel images with a standard camera and lens. More importantly, our novel viewer enables exploration of such images at interactive rates over a network, while dynamically and smoothly interpolating the projection between perspective and curved projections, and simultaneously modifying the tone-mapping to ensure an optimal view of the portion of the scene being viewed.publishe

Documenting Paintings Using Gigapixel SfM Photogrammetry

[EN] Capturing paintings with gigapixel resolution (resolution around 1000 megapixels or greater) is an innovative technique that is starting to be used by some important international museums for documenting, analysing, and disseminating their masterpieces. This line of research is extremely interesting, not only for art curators and scholars, but also for the general public. The results can be disseminated through online virtual tours, offering a detailed interactive visualization. These virtual tours allow the viewer to delve into the artwork, in such a way, that it is possible to zoom in and observe those details, which would be negligible to the naked eye in a real visit. Therefore, this kind of virtual visualization using gigapixel images becomes an essential tool to enhance this cultural heritage and to make it accessible to everyone. This article will describe an affordable methodology, based on SfM photogrammetry techniques, with which it will be possible to achieve a very high level of detail and chromatic fidelity, when documenting and disseminating pictorial artworks. As a practical example, there will be shown a case study of the altarpiece, from the Museo de Bellas Artes de Valencia (Spain), entitled Virgen de las fiebres, painted around 1500 by Bernardino di Benedetto di Biagio, nicknamed `Il Pinturicchio' (Perugia, ca. 1454 ¿ Siena, 1513).This research was carried out within the Research Project entitled Captura fotográfica de resolución gigapíxel para la documentación y divulgación del patrimonio pictórico (01/01/19- 01/01/21), reference SP20180066. Project funded with the help of Primeros Proyectos de Investigación (PAID-06-18), Vicerrectorado de Investigación,Innovación y Transferencia de la Universitat Politècnica de València (UPV), València, SpainCabezos Bernal, PM.; Rodríguez Navarro, P.; Gil Piqueras, T. (2021). Documenting Paintings Using Gigapixel SfM Photogrammetry. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 93-100. https://doi.org/10.5194/isprs-archives-XLVI-M-1-2021-93-20219310

KNOWLEDGE AND DOCUMENTATION OF RENAISSANCE WORKS OF ART: THE REPLICA OF THE “ANNUNCIATION” BY BEATO ANGELICO

The Annunciation by Guido di Pietro from Mugello, known as Beato Angelico, is a wide tempera painting with some fine gold foil placed on a wooden support, today hosted at the Museum of the Basilica of Santa Maria delle Grazie, in San Giovanni Valdarno. On the occasion of the exhibition “Masaccio e Angelico. Dialogo sulla verità nella pittura”, the museum asked to the Department of Architecture at the University of Bologna to develop a digital high-resolution surrogate to favour deep investigations, to plan restoration and to simply tell the stories behind the artwork. Two tasks were accomplished: to let visitors discover the secrets in the painting and to let scholars study the artwork, to better understand the masterpiece. This paper introduces the outcomes of the research developed to digitize the Annunciation, following a dedicated pipeline developed to improve the fruition of its digital replica, originated from different input sources, and surrogating the user experience on the real object. This work presents a method for the 3D reconstruction of the surfaces based on different techniques for elements with different depth resolutions (i.e., the painting and the wooden frame) which combine photogrammetry and photometric stereo exploiting both procedures and pushing forward the boundaries of Gigapixel Imaging and photogrammetric-based 3D model representation

Progressive Refinement Imaging

This paper presents a novel technique for progressive online integration of uncalibrated image sequences with substantial geometric and/or photometric discrepancies into a single, geometrically and photometrically consistent image. Our approach can handle large sets of images, acquired from a nearly planar or infinitely distant scene at different resolutions in object domain and under variable local or global illumination conditions. It allows for efficient user guidance as its progressive nature provides a valid and consistent reconstruction at any moment during the online refinement process. // Our approach avoids global optimization techniques, as commonly used in the field of image refinement, and progressively incorporates new imagery into a dynamically extendable and memory‐efficient Laplacian pyramid. Our image registration process includes a coarse homography and a local refinement stage using optical flow. Photometric consistency is achieved by retaining the photometric intensities given in a reference image, while it is being refined. Globally blurred imagery and local geometric inconsistencies due to, e.g. motion are detected and removed prior to image fusion. // We demonstrate the quality and robustness of our approach using several image and video sequences, including handheld acquisition with mobile phones and zooming sequences with consumer cameras