Research and Implementation of Driving Concern Area Detection Based on Deep Learning

Authors

Jihua Ye, College of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, China;
Shuxia Shi, College of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, China;
Hanxi Li, College of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, China;
Shimin Wang, College of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, China;
Siyu Yang, College of Computer Information and Engineering, Jiangxi Normal University, Nanchang 330022, China;

Abstract

Abstract: As a key technology of intelligent driving, driving concern area detection method has an important impact on the performance of intelligent driving or intelligent early warning system. In view of the shortcomings of the existing methods, this paper proposes an effective method for driving concern area detection based on the deep learning. We obtain the camera internal and external parameters by using camera self-calibration method based on camera model, use the Canny edge detection and Bisecting K-means clustering to realize the vanishing point estimation, and establish the road detection model based on the obtained estimates. We obtain the depth features from the SSD model training, use the convolution layer of SSD which combines with the upper sampling layer of FCN8 to detect the region of the road surface. The experimental results show that compared with the existing methods, the proposed method not only has better road detection effect, but also can detect the road area of the shaded part more accurately.

Recommended Citation

Ye, Jihua; Shi, Shuxia; Li, Hanxi; Wang, Shimin; and Yang, Siyu (2019) "Research and Implementation of Driving Concern Area Detection Based on Deep Learning," Journal of System Simulation: Vol. 31: Iss. 7, Article 20.
DOI: 10.16182/j.issn1004731x.joss.18-CVR0694
Available at: https://dc-china-simulation.researchcommons.org/journal/vol31/iss7/20

First Page

1421

Revised Date

2018-10-19

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.18-CVR0694

Last Page

1428

CLC

TP391

Recommended Citation

Ye Jihua, Shi Shuxia, Li Hanxi, Wang Shimin, Yang Siyu. Research and Implementation of Driving Concern Area Detection Based on Deep Learning[J]. Journal of System Simulation, 2019, 31(7): 1421-1428.

DOI

10.16182/j.issn1004731x.joss.18-CVR0694