Examinando por Autor "Ogáyar, Carlos Javier"
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Ítem Estrategias para la gestión a gran escala de nubes de puntos(2024-07-19) Béjar, Juan Antonio; Rueda-Ruiz, Antonio Jesús; Ogáyar, Carlos Javier; Universidad de Jaén. Departamento de InformáticaLos modelos de nubes de puntos se han convertido en una herramienta de gran importancia en multitud de dominios. Las mejoras asociadas a las tecnologías de escaneo han generado una amplia disponibilidad de modelos de alta resolución. La necesidad de definir nuevas estrategias que faciliten la organización, almacenamiento y posterior acceso a esta información es cada vez más apremiante. En esta tesis tratamos de proponer una nueva alternativa con la que resolver múltiples de estas problemáticas. Presentamos SPSLiDAR, un modelo sencillo y flexible que permite registrar modelos de nubes de puntos a escala global y a lo largo del tiempo, capaz de modelar distintas estructuras en base a las cuáles organizar la información de una nube de puntos. Trabajamos en la integración de estos conceptos en una solución real en forma de repositorio de nubes de puntos, analizando distintas estructuras de datos además del comportamiento de distintos sistemas de almacenamiento. Point cloud models have become a valuable source of information in multiple domains. The improvements related with scanning technologies throughout the last decade have made easier the access to detailed high-resolution point cloud models. However, this increase in the volume of information has posed challenges with regards to the storage, structuring, and access to this information. In this thesis we propose SPSLiDAR, a simple and flexible model that allows to register point cloud models acquired at a global level at any time. This model allows to structure a point cloud in multiple ways, being able to adapt to different use cases. We work on the integration of all these concepts in a real solution, building a point cloud repository. We propose multiple data structures compatible with SPSLiDAR that fit different scenarios. We also analyze different storage systems for the persistence of point clouds and its related information.Ítem SPSLiDAR: towards a multi-purpose repository for large scale LiDAR datasets(Taylor & Francis, 2022-03) Rueda-Ruiz, Antonio Jesús; Ogáyar, Carlos Javier; Segura-Sánchez, Rafael; Béjar, Juan Antonio; Delgado-García, JorgeThe widespread use of LiDAR technology in a multitude of domains has produced a growing availability of massive high-resolution point datasets that demand new approaches for efficient organization and storage, filtering using different spatio-temporal criteria, selective/progressive visualization, processing and analysis, and collaborative editing. Ideally, LiDAR data coming from multiple sources and organized in different datasets should be accessible in a simple, uniform, and ubiquitous way to comply with the FAIR principle proposed by the Open Geospatial Consortium: Findable, Accessible, Interoperable, and Reusable. With this goal in mind, we present SPSLiDAR, a conceptual model with a simple interface for repositories of LiDAR data that can be adapted to the needs of different applications. SPSLiDAR includes aspects, such as the arrangement of related datasets into workspaces on a world scale, support for overlapping datasets with different resolutions or acquired at different times, and hierarchical organization of point data, enabling levels of detail and selective download. We also describe in detail an implementation of this model aimed at visualization and downloading of large datasets using the MongoDB database. Finally, we show some experimental results of this implementation using real data, such as its space requirements, upload latency, access latency, and throughput.