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Hemispherical Gaussians for Accurate Light Integration Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Scene Recognition for Indoor Localization of Mobile Robots Using Deep CNN

Authors : Piotr Wozniak, Hadha Afrisal, Rigel Galindo Esparza, Bogdan Kwolek

Published in: Computer Vision and Graphics

Publisher: Springer International Publishing

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Abstract

In this paper we propose a deep neural network based algorithm for indoor place recognition. It uses transfer learning to retrain VGG-F, a pretrained convolutional neural network to classify places on images acquired by a humanoid robot. The network has been trained as well as evaluated on a dataset consisting of 8000 images, which were recorded in sixteen rooms. The dataset is freely accessed from our website. We demonstrated experimentally that the proposed algorithm considerably outperforms BoW algorithms, which are frequently used in loop-closure. It also outperforms an algorithm in which features extracted by FC-6 layer of the VGG-F are classified by a linear SVM.

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Metadata
Title
Scene Recognition for Indoor Localization of Mobile Robots Using Deep CNN
Authors
Piotr Wozniak
Hadha Afrisal
Rigel Galindo Esparza
Bogdan Kwolek
Copyright Year
2018
Book
Computer Vision and Graphics

Print ISBN: 978-3-030-00691-4

Electronic ISBN: 978-3-030-00692-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-00692-1_13

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