Examinando por Materia "3D and 2D feature descriptors"

Mostrando1 - 1 de 1
  • Miniatura
    Publicación
    Acceso abierto
    Reconocimiento de elementos de escena sobre nubes de puntos tridimensionales en aplicaciones de robótica móvil terrestre.
    (Universidad de Ibagué, 2019) Florez Romero, Andres Mauricio; Murcia Moreno, Harold Fabián
    This project is developed in the seedbed SI2C of the research group D+TEC of the Universidad de Ibagué, it consists on the a supervised classification algorithm for scene elements recognition on urban environments, taking points clouds acquired with an acquisition system that implements in LAAS (Laboratory for Analysis and Architecture of Systems) that implements a LiDAR sensor on board a UGV. The classifiers were Random Forest (RF), Support Vector Machine (SVM), AdaBoost, Neural Network (NN) and Gaussian Naive Bayes, those were trained with 3D features, 2D and characteristics of full wave form information, the last one being the contribution generated for projects already developed. The classifiers were evaluated using the F1 Score indicator, obtaining an average of scores up to 86% accuracy getting a classifier with rates of high success and demonstrating the contribution provided by the descriptors proposed based on the information obtained from the full wave characteristics, respect to conventional descriptors