3D Object Recognition with Convolutional Neural Network
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http://hdl.handle.net/10045/57438
Título: | 3D Object Recognition with Convolutional Neural Network |
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Autor/es: | Garcia-Garcia, Alberto |
Director de la investigación: | García Rodríguez, José | Pomares, Jorge |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación | Universidad de Alicante. Departamento de Física, Ingeniería de Sistemas y Teoría de la Señal |
Palabras clave: | Deep Learning | 3D Object Recognition | Convolutional Neural Networks | Caffe | Point Cloud Library |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores | Ingeniería de Sistemas y Automática |
Fecha de publicación: | 1-sep-2016 |
Fecha de lectura: | 6-jun-2016 |
Resumen: | In this work, we propose the implementation of a 3D object recognition system using Convolutional Neural Networks. For that purpose, we first analyzed the theoretical foundations of that kind of neural networks. Next, we discussed ways of representing 3D data in a compact and structured manner to feed the neural network. Those representations consist of a grid-like structure (fixed and adaptive) and a measure for the occupancy of each cell of the grid (binary, normalized point density, and surface intersection). At last, 2.5D and 3D Convolutional Neural Network architectures were implemented and tested using those volumetric representations. The experimentation included an in-depth study of their performance in synthetically simulated adverse conditions that characterize the real-world, i.e., noise and occlusions. The resulting system, the best one out of that experimentation, is able to efficiently recognize objects in three dimensions with a success rate of 85% in a common household CAD objects dataset. |
URI: | http://hdl.handle.net/10045/57438 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/masterThesis |
Derechos: | Licencia Creative Commons Reconocimiento-CompartirIgual 4.0 |
Revisión científica: | no |
Aparece en las colecciones: | Máster Universitario en Automática y Robótica - Trabajos Fin de Máster |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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3D_Convolutional_Neural_Network_for_Viewbased_Objec_Garcia_Garcia_Alberto.pdf | 9,75 MB | Adobe PDF | Abrir Vista previa | |
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