Traffic Scenes Classification for Self-driving Car
- https://doi.org/10.2991/icsmim-15.2016.25How to use a DOI?
- Traffic Scenes Classification, Self-driving Car, Road Network Definition
In this paper, machine learning model is applied to label the attributes of traffic scenes automatically in the RNDF (Road Network Definition File), which is used in the self-driving car. The “gist” features extracted from one image of the video stream are used as the model’s input. In the experiments, the test model is SVM (Support Vector Machine) and the training and test samples are from the FM2 database. The experiments verify the feasibility and effectiveness of this method.
- © 2016, 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 - Hongbo Lv AU - Xiaolin Zhuang AU - Huifang Cao PY - 2016/01 DA - 2016/01 TI - Traffic Scenes Classification for Self-driving Car BT - Proceedings of the 2015 4th International Conference on Sensors, Measurement and Intelligent Materials PB - Atlantis Press SP - 130 EP - 133 SN - 2352-538X UR - https://doi.org/10.2991/icsmim-15.2016.25 DO - https://doi.org/10.2991/icsmim-15.2016.25 ID - Lv2016/01 ER -