NDLI: Homography-based traffic sign localisation and pose estimation from image sequence

Content Provider	IET Digital Library
Author	Cui, Zhichao Liu, Yuehu Ren, Fuji
Abstract	This study proposes a vision-based method for traffic sign attribute estimation, i.e. 3D position and pose, from image sequences by binocular or monocular cameras. The method starts with acquiring robust feature correspondences based on homography constraints from image pairs. Then the objective function is designed to integrate the feature correspondences to optimise the parameters of the traffic sign plane in the 3D coordinate. Finally, the sign plane is utilised for attribute estimation. In addition, the authors provide an extension for the raw KITTI dataset, which can be utilised for 3D tasks of traffic sign localisation and pose estimation. In the experiments, three popular methods are employed for comparisons based on the publicly available BelgiumTS and KITTI datasets. The results show that the authors’ method based on SIFT and SURF features can locate the traffic signs with a mean error of ∼0.44 and 0.51 m in the BelgiumTS and KITTI datasets, respectively, and estimate the pose with a mean error of ∼14.45° in the KITTI dataset.
Starting Page	2829
Ending Page	2839
Page Count	11
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 14, Dec (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/14
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2019.0023
Journal	IET Image Processing
Publisher Date	2019-07-09
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Attribute Estimation Binocular Cameras Camera Computer Vision Computer Vision And Image Processing Technique Feature Extraction Gradient Method Homography Constraint Homography-based Traffic Sign Localisation Image Classification Image Matching Image Pairs Image Recognition Image Sequence Monocular Cameras Object Detection Object Recognition Objective Function Pose Estimation Raw KITTI Dataset Robust Feature Correspondences SIFT Size 0.44 M Size 0.51 M SURF Traffic Engineering Computing Traffic Sign Plane Video Signal Processing Vision-based Method
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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