NDLI: Joint vehicle detection and distance prediction via monocular depth estimation

Content Provider	IET Digital Library
Author	Shen, Chao Zhao, Xiangmo Liu, Zhanwen Gao, Tao Xu, Jiang
Abstract	Vehicle detection and distance estimation are critical components of driver assistance system and self-driving system, and considerable different frameworks have been investigated such as radar, laser and camera-based. Among them, camera-based vehicle detection and distance estimation have an obvious advantage over other systems in that it needs lower cost. However, existing camera-based methods are not robust enough under complex driving scenes. In this work, an end-to-end deep convolutional neural network framework is proposed to jointly detect vehicles and estimate vehicle distance efficiently. Specifically, a monocular depth estimation method is designed to transform the RGB appearance information into depth modality information. Then the vehicle detection module takes the RGB and depth image as inputs to improve the detection performance. Finally, the distance estimation module employs the detection results and the estimated depth information to predict the distance more precisely. The whole network can be trained in an end-to-end manner with the multi-task loss function. The proposed framework is evaluated on the public vehicle detection benchmark KITTI to show the effectiveness of the proposed framework. Moreover, the performance of three proposed sub-modules are also analysed separately to give a more comprehensive evaluation of the designed framework.
Starting Page	753
Ending Page	763
Page Count	11
ISSN	1751956X
Volume Number	14
e-ISSN	17519578
Issue Number	Issue 7, Jul (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-its/14/7
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-its.2019.0376
Journal	IET Intelligent Transport Systems
Publisher Date	2020-03-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Camera Camera-based Vehicle Detection Complex Driving Scenes Computer Vision Computer Vision And Image Processing Technique Convolutional Neural Nets Critical Component Depth Image Depth Modality Information Detection Performance Distance Estimation Module Driver Assistance System Driver Information System End-to-end Deep Convolutional Neural Network Framework Estimated Depth Information Image Colour Analysis Image Sonsor Joint Vehicle Detection Monocular Depth Estimation Method Neural Computing Technique Object Detection Optical, Image And Video Signal Processing Public Vehicle Detection Benchmark KITTI RGB Appearance Information Road Vehicle Self-driving System Traffic Engineering Computing Vehicle Detection Module Vehicle Distance
Content Type	Text
Resource Type	Article
Subject	Law Transportation Environmental Science Mechanical Engineering

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Vision-based inter-vehicle distance estimation for driver alarm system

3D driver pose estimation based on joint 2D–3D network

Fully convolutional multi-scale dense networks for monocular depth estimation

Scale-aware limited deformable convolutional neural networks for traffic sign detection and classification

Real-time detection of distracted driving based on deep learning

Technology and application of intelligent driving based on visual perception

Three-stage RGBD architecture for vehicle and pedestrian detection using convolutional neural networks and stereo vision

Lateral distance detection model based on convolutional neural network

RGB-D static gesture recognition based on convolutional neural network

Joint vehicle detection and distance prediction via monocular depth estimation

Similar Documents

Vision-based inter-vehicle distance estimation for driver alarm system

3D driver pose estimation based on joint 2D–3D network

Fully convolutional multi-scale dense networks for monocular depth estimation

Scale-aware limited deformable convolutional neural networks for traffic sign detection and classification

Real-time detection of distracted driving based on deep learning

Technology and application of intelligent driving based on visual perception

Three-stage RGBD architecture for vehicle and pedestrian detection using convolutional neural networks and stereo vision

Lateral distance detection model based on convolutional neural network

RGB-D static gesture recognition based on convolutional neural network

Joint vehicle detection and distance prediction via monocular depth estimation