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

Dmitry Yudin, Anton Sotnikov, Andrey Krishtopik

Результат исследований: Глава в книге, отчете, сборнике статейМатериалы для конференциирецензирование

5 Цитирования (Scopus)

Аннотация

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.

Язык оригиналаАнглийский
Название основной публикацииProceedings - 2019 International Conference on Artificial Intelligence
Подзаголовок основной публикацииApplications and Innovations, IC-AIAI 2019
РедакторыSergei Prokhorov
ИздательInstitute of Electrical and Electronics Engineers Inc.
Страницы100-103
Число страниц4
ISBN (электронное издание)9781728143262
DOI
СостояниеОпубликовано - сент. 2019
Опубликовано для внешнего пользованияДа
Событие2019 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2019 - Belgrade, Сербия
Продолжительность: 30 сент. 20194 окт. 2019

Серия публикаций

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

Конференция

Конференция2019 International Conference on Artificial Intelligence: Applications and Innovations, IC-AIAI 2019
Страна/TерриторияСербия
ГородBelgrade
Период30/09/194/10/19

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