Publicação

Point Cloud Coding: Adopting a Deep Learningbased Approach

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Detalhes bibliográficos
Resumo:Point clouds have recently become an important visual representation format, especially for virtual and augmented reality applications, thus making point cloud coding a very hot research topic. Deep learning-based coding methods have recently emerged in the field of image coding with increasing success. These coding solutions take advantage of the ability of convolutional neural networks to extract adaptive features from the images to create a latent representation that can be efficiently coded. In this context, this paper extends the deep-learning coding approach to point cloud coding using an autoencoder network design. Performance results are very promising, showing improvements over the Point Cloud Library codec often taken as benchmark, thus suggesting a significant margin of evolution for this new point cloud coding paradigm.
Autores principais:Guarda, André
Outros Autores:M. M. Rodrigues, Nuno; Pereira, Fernando
Assunto:point cloud coding deep learning convolutional neural network
Ano:2019
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Instituto Politécnico de Leiria
Idioma:inglês
Origem:IC-online
Descrição
Resumo:Point clouds have recently become an important visual representation format, especially for virtual and augmented reality applications, thus making point cloud coding a very hot research topic. Deep learning-based coding methods have recently emerged in the field of image coding with increasing success. These coding solutions take advantage of the ability of convolutional neural networks to extract adaptive features from the images to create a latent representation that can be efficiently coded. In this context, this paper extends the deep-learning coding approach to point cloud coding using an autoencoder network design. Performance results are very promising, showing improvements over the Point Cloud Library codec often taken as benchmark, thus suggesting a significant margin of evolution for this new point cloud coding paradigm.