Virtualized Point Cloud Rendering
IEEE Transactions on Visualization and Computer Graphics
Publications
You can also find my articles on my Google Scholar and ORCID profile.
Journal Articles
Enhancing LiDAR point cloud generation with BRDF-based appearance modelling
ISPRS Journal of Photogrammetry and Remote Sensing
Generating implicit object fragment datasets for machine learning
Computers & Graphics
Detection of landscape features with visible and thermal imaging at the Castle of Puerta Arenas
Archaeological and Anthropological Sciences
Efficient generation of occlusion-aware multispectral and thermographic point clouds
Computers and Electronics in Agriculture
Metaheuristics for the optimization of Terrestrial LiDAR set-up
Automation in Construction
Nested spatial data structures for optimal indexing of LiDAR data
ISPRS Journal of Photogrammetry and Remote Sensing
A GPU-Accelerated Framework for Simulating LiDAR Scanning
IEEE Transactions on Geoscience and Remote Sensing
Remote sensing image fusion on 3D scenarios: A review of applications for agriculture and forestry
International Journal of Applied Earth Observation and Geoinformation
Reconstruction of tree branching structures from UAV-LiDAR data
Frontiers in Environmental Science
An optimized approach for generating dense thermal point clouds from UAV-imagery
ISPRS Journal of Photogrammetry and Remote Sensing
A framework for registering UAV-based imagery for crop-tracking in Precision Agriculture
International Journal of Applied Earth Observation and Geoinformation
International Conferences
Automatic Agrivoltaic Site Selection: a User-Friendly Interface powered by AHP Multicriteria Decision-Making
41st European Photovoltaic Solar Energy Conference and Exhibition
SAM-Based Detection of Structural Anomalies in 3D Models for Preserving Cultural Heritage
19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2024)
GPU-based Mapping of Thermal Imagery for Generating 3D Occlusion-Aware Point Clouds
IGARSS - IEEE International Geoscience and Remote Sensing Symposium
Modeling and Enhancement of LiDAR Point Clouds from Natural Scenarios
Eurographics - Posters
National Conferences
Kalathos+: Construcción de datasets para la clasificación automática de fragmentos de vasijas cerámicas de torno
Congreso Español de Informática Gráfica (CEIG)
Guided Modeling of Natural Scenarios: Vegetation and Terrain
Congreso Español de Informática Gráfica (CEIG)
A GPU-accelerated LiDAR Sensor for Generating Labelled Datasets
Congreso Español de Informática Gráfica (CEIG)
Comparison of GPU-based Methods for Handling Point Cloud Occlusion
Congreso Español de Informática Gráfica (CEIG)
Multispectral Registration, Undistortion and Tree Detection for Precision Agriculture
Congreso Español de Informática Gráfica (CEIG)
Thesis
Nuevas herramientas para la modelización de datos procedentes de sensores/New tools for modelling sensor data
RUJA: Repositorio Institucional de Producción Científica de la Universidad de Jaén
Supervisors: Francisco-Ramón Feito-Higueruela, Carlos-Javier Ogáyar-Anguita
Simulación de escaneados 3D
CREA: Colección de Recursos Educativos Abiertos de la Universidad de Jaén
Supervisors: Carlos-Javier Ogáyar-Anguita, Francisco-Ramón Feito-Higueruela
Prototipo de control avanzado de grandes plantaciones mediante teledetección
CREA: Colección de Recursos Educativos Abiertos de la Universidad de Jaén
Supervisors: Francisco-Ramón Feito-Higueruela, Carlos-Javier Ogáyar-Anguita
Datasets
Voxelized fragment dataset for machine learning
Voxelized fragments from high-resolution 3D models, curated as training data for machine learning. The Zenodo record contains compressed binary voxel grids generated from 1,052 Iberian vessels, with class metadata; the complete dataset with point clouds and triangle meshes is hosted separately by CEATIC.
Related publication: Generating implicit object fragment datasets for machine learning
UAV-based hyperspectral images of seventeen red and white grapevine varieties
Hyperspectral UAV imagery covering seventeen grapevine varieties, grouped into red and white cultivars. The dataset is provided in its original non-rectified form with header files, RGB extracts for quick inspection, and labels prepared from NDVI-derived masks in Sensarea.
Related publication: Classification of Grapevine Varieties Using UAV Hyperspectral Imaging