Deep learning in vehicle pose recognition on two-dimensional images

Dmitry Yudin, Ekaterina Kapustina

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The paper describes usage of deep neural network architectures such as VGG, ResNet and InceptionV3 for the classification of small images. Each image may contain one of four vehicle pose categories or background. An iterative procedure for training a neural network is proposed, which allows us to quickly tune the network using wrongly classified images on test sample. A dataset of more than 23,000 marked images was prepared, of which 70% of images were used as a training sample, 30% as a test sample. On the test sample, the trained deep convolutional neural networks are ensured the recognition accuracy for all classes of at least 93.9%, the classification precision for different vehicle poses and background was from 85.29% to 100.0%, the recall was from 81.9% to 100.0%. The computing experiment was carried out on a graphics processor using NVIDIA CUDA technology. It showed that the average processing time of one image varies from 3.5 ms to 15.9 ms for different architectures. Obtained results can be used in software for image recognition of road conditions for unmanned vehicles and driver assistance systems.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Scientific Conference “Intelligent Information Technologies for Industry” (IITI’18) - Volume 2
EditorsValery Tarassov, Sergey Kovalev, Andrey Sukhanov, Ajith Abraham, Vaclav Snasel
PublisherSpringer Verlag
Pages126-137
Number of pages12
ISBN (Print)9783030018207
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event3rd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2018 - Sochi, Russian Federation
Duration: 17 Sep 201821 Sep 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume875
ISSN (Print)2194-5357

Conference

Conference3rd International Scientific Conference on Intelligent Information Technologies for Industry, IITI 2018
Country/TerritoryRussian Federation
CitySochi
Period17/09/1821/09/18

Keywords

  • Classification
  • Convolutional neural network
  • Deep learning
  • Image recognition
  • Vehicle pose

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