3D pointcloud processing using artificial intelligence and high performance computing techniques

• Autores: Alberto Manuel Esmorís Pena
• Directores de la Tesis: David López Vilariño (dir. tes.), Francisco Fernández Rivera (dir. tes.)
• Lectura: En la Universidade de Santiago de Compostela ( España ) en 2024
• Idioma: inglés
• Tribunal Calificador de la Tesis: Pedro Arias Sánchez (presid.), Margarita Amor (secret.), David Expósito Singh (voc.)
• Programa de doctorado: Programa de Doctorado en Investigación en Tecnologías de la Información por la Universidad de A Coruña y la Universidad de Santiago de Compostela
• Materias:
  • Matemáticas
    • Ciencia de los ordenadores
      • Inteligencia artificial
      • Calculo digital
• Enlaces
  • Tesis en acceso abierto en: MINERVA
• Resumen

  • This thesis studies 3D point cloud processing as a challenge for computer science. High-performance computing techniques and artificial intelligence models are explored as the main strategies for efficiently processing 3D point clouds. Some tasks approached in this thesis are terrain segmentation, unsupervised clustering, analysis of crossing zones in urban contexts, classification of curb points and their interpolation, boundary segmentation, classical machine learning methods for point-wise classification, deep-learning models for point-wise classification and roughness estimation, and road bump detection through surface fitting method