Beyond Controlled Environments: 3D Camera Re-Localization in Changing Indoor Scenes

Long-term camera re-localization is an important task with numerous computer vision and robotics applications. Whilst various outdoor benchmarks exist that target lighting, weather and seasonal changes, far less attention has been paid to appearance changes that occur indoors. This has led to a mismatch between popular indoor benchmarks, which focus on static scenes, and indoor environments that are of interest for many real-world applications. In this paper, we adapt 3RScan - a recently introduced indoor RGB-D dataset designed for object instance re-localization - to create RIO10, a new long-term camera re-localization benchmark focused on indoor scenes. We propose new metrics for evaluating camera re-localization and explore how state-of-the-art camera re-localizers perform according to these metrics. We also examine in detail how different types of scene change affect the performance of different methods, based on novel ways of detecting such changes in a given RGB-D frame. Our results clearly show that long-term indoor re-localization is an unsolved problem. Our benchmark and tools are publicly available at waldjohannau.github.io/RIO10Comment: ECCV 2020, project website https://waldjohannau.github.io/RIO1

Looking for the more favourable similarity between graphic images

The processes of a projective nature, through the construction of images, both rigor-ous and expressive, make it possible to translate the spatial qualities and figurative properties of the space that surrounds us on the level of design, making it possible for those who read the image, the recognition of the object of the space. The model that is created, as a conventional image of objective reality, uses a linguistic code with a precise system of rules. The work presented here, in tents, illustrates, within the code of projective transformations, that operation that transforms on the plane (or rather on a plane π ≡ π’) the same relations that exist between the figures in the perspecti-ve, the homology, understood as the process capable of creating an image in which the original one is recognizable in its transformed, preserves its characteristics, and from it we are able to re-cognize, backwards, the initial image

Looking for the More Favourable Similarity Between Graphic Images

The processes of a projective nature, through the construction of images, both rigorous and expressive, make it possible to translate the spatial qualities and figurative properties of the space that surrounds us on the level of design, making it possible for those who read the image, the recognition of the object of the space. The model that is created, as a conventional image of objective reality, uses a linguistic code with a precise system of rules. The work presented here, in tents, illustrates, within the code of projective transformations, that operation that transforms on the plane (or rather on a plane p p’) the same relations that exist between the figures in the perspective, the homology, understood as the process capable of creating an image in which the original one is recognizable in its transformed, preserves its characteristics, and from it we are able to recognize, backwards, the initial image

Mapas de suelos de las provincias de Zaragoza, Huesca y Logroño. Memoria explicativa

Escala 1: 250.000.-- Descripción de suelos.-- Contiene mapas al final.Dentro de la línea de trabajo sobre clasificación y cartografía de suelos del Instituto Nacional de Edafología, aparece ahora el estudio de los suelos y su representación cartográfica a escala 1:250.000 de las provincias de Logroño, Zaragoza y Huesca.Peer reviewe

Teledetección y SIG en la Planificación Ambiental. El ejemplo de Espinoso del Rey

V Reunión Científica de la Asociación Española de Teledetección, Las Palmas de Gran Canaria, España, 10-12 de Noviembre.Peer reviewe

The relationship between real and illusory architecture: survey and analysis of the ex-refectory of Orsoline's convent in Rome

The subject of this work is the study of perspective scenes frescoed in the ex-refectory of an important cloister in the centre of Rome, with the aim of understanding the relationship between real and illusory space through a combination of architectural survey techniques

Automatic Virtual Reconstruction of Historic Buildings Through Deep Learning. A Critical Analysis of a Paradigm Shift

New advances in the field of artificial intelligence propose to rethink methodologies in many areas of knowledge. In the field of Architectural Heritage studies, the virtual reconstruction of historical buildings in ruins has maintained the same analysis methodology for centuries. New technologies have been adding tools to the reconstruction process, which still depends on the theoretical assumption of a specialist. However, the development of neural networks (Deep Learning) is proposing a radical change in the analysis and reconstruction methodology. The proposal described as automatic virtual reconstruction uses Generative Adversarial Networks (GAN) and Natural Processing Language (NPL) technology for training networks and learning patterns of a specific architectural style. A comparative study of the two methods can enlighten on the possibilities that will emerge in the coming years. This paradigm shift in the virtual reconstruction of historic buildings can revolutionize, from a scientific and informative point of view, the way of understanding and interpreting architectural heritage