Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks
Boyang Su, Jie Shao, Jianying Zhou, Xiaoteng Zhang, Lin Mei
Available Online December 2015.
- 10.2991/jimet-15.2015.147How to use a DOI?
- Vehicle Color Recognition, Deep Convolutional Nerual Networks, network in network.
Vehicle information extraction is the key means in Intelligent Transportation System (ITS). Color plays an important role in vehicle recognition. The main challenge of vehicle color recognition is to find the dominant color. In this paper, we propose a color recognition method using convolutional neural network. We train the classifier with the network structure „NIN to increase the classification accuracy. The experiments are validated on our dataset and extra data, which are collected from city surveillance equipment. The proposed method outperforms other competing color recognition methods.
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Boyang Su AU - Jie Shao AU - Jianying Zhou AU - Xiaoteng Zhang AU - Lin Mei PY - 2015/12 DA - 2015/12 TI - Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks BT - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference PB - Atlantis Press SP - 790 EP - 793 SN - 2352-538X UR - https://doi.org/10.2991/jimet-15.2015.147 DO - 10.2991/jimet-15.2015.147 ID - Su2015/12 ER -