Detection of Big Animals on Images with Road Scenes using Deep Learning

Dmitry Yudin, Anton Sotnikov, Andrey Krishtopik

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

5 Citations (Scopus)

Abstract

The recognition of big animals on the images with road scenes has received little attention in modern research. There are very few specialized data sets for this task. Popular open data sets contain many images of big animals, but the most part of them is not correspond to road scenes that is necessary for on-board vision systems of unmanned vehicles. The paper describes the preparation of such a specialized data set based on Google Open Images and COCO datasets. The resulting data set contains about 20000 images of big animals of 10 classes: 'Bear', 'Fox', 'Dog', 'Horse', 'Goat', 'Sheep', 'Cow', 'Zebra', 'Elephant', 'Giraffe'. Deep learning approaches to detect these objects are researched in the paper. Authors trained and tested modern neural network architectures YOLOv3, RetinaNet R-50-FPN, Faster R-CNN R-50-FPN, Cascade R-CNN R-50-FPN. To compare the approaches the mean average precision (mAP) was determined at IoU≥50%, also their speed was calculated for input tensor sizes 640x384x3. The highest quality metrics are demonstrated by architecture YOLOv3 as for ten classes (0.78 mAP) and one joint class (0.92 mAP) detection with speed more 35 fps on NVidia Tesla V-100 32GB video card. At the same hardware, the RetinaNet R-50-FPN architecture provided recognition speed of more than 44 fps and a 13% lower mAP. The software implementation was done using the Keras and PyTorch deep learning libraries and NVidia CUDA technology. The proposed data set and neural network approach to recognizing big animals on images have shown their effectiveness and can be used in the on-board vision systems of driverless cars or in driver assistant systems.

Original languageEnglish
Title of host publicationProceedings - 2019 International Conference on Artificial Intelligence
Subtitle of host publicationApplications and Innovations, IC-AIAI 2019
EditorsSergei Prokhorov
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages100-103
Number of pages4
ISBN (Electronic)9781728143262
DOIs
Publication statusPublished - Sep 2019
Externally publishedYes
Event2019 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2019 - Belgrade, Serbia
Duration: 30 Sep 20194 Oct 2019

Publication series

NameProceedings - 2019 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2019

Conference

Conference2019 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2019
Country/TerritorySerbia
CityBelgrade
Period30/09/194/10/19

Keywords

  • big animals
  • data set
  • deep learning
  • detection
  • image recognition
  • neural network
  • road scene
  • software

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