BoxCars: 3D Boxes as CNN Input for Improved Fine-Grained Vehicle Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F16%3APU121605" target="_blank" >RIV/00216305:26230/16:PU121605 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/7780697/" target="_blank" >http://ieeexplore.ieee.org/document/7780697/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CVPR.2016.328" target="_blank" >10.1109/CVPR.2016.328</a>
Alternative languages
Result language
angličtina
Original language name
BoxCars: 3D Boxes as CNN Input for Improved Fine-Grained Vehicle Recognition
Original language description
We are dealing with the problem of fine-grained vehicle make&model recognition and verification. Our contribution is showing that extracting additional data from the video stream - besides the vehicle image itself - and feeding it into the deep convolutional neural network boosts the recognition performance considerably. This additional information includes: 3D vehicle bounding box used for "unpacking" the vehicle image, its rasterized low-resolution shape, and information about the 3D vehicle orientation. Experiments show that adding such information decreases classification error by 26% (the accuracy is improved from 0.772 to 0.832) and boosts verification average precision by 208% (0.378 to 0.785) compared to baseline pure CNN without any input modifications. Also, the pure baseline CNN outperforms the recent state of the art solution by 0.081. We provide an annotated set "BoxCars" of surveillance vehicle images augmented by various automatically extracted auxiliary information. Our approach and the dataset can considerably improve the performance of traffic surveillance systems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/TE01020155" target="_blank" >TE01020155: Transport systems development centre</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
ISBN
978-1-4673-8851-1
ISSN
1063-6919
e-ISSN
—
Number of pages
10
Pages from-to
3006-3015
Publisher name
IEEE Computer Society
Place of publication
Las Vegas
Event location
Las Vegas
Event date
Jun 26, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000400012303008