NDLI: A Method to Calibrate Vehicle-Mounted Cameras Under Urban Traffic Scenes

Content Provider	IEEE Xplore Digital Library
Author	Yaonan Wang Xiao Lu Zhigang Ling Yimin Yang Zhenjun Zhang Kena Wang
Copyright Year	2000
Abstract	We address the problem of vehicle-mounted camera calibration under urban traffic scenes regarding the fact that the traditional calibration methods are practically restricted, since the internal parameters should be calibrated in the laboratory and it is impossible for recalibration that resulted from the parameters drifting or re-focusing when driving on roads. In this paper, we propose to utilize the manual lines lying in Manhattan directions in the scenes to compute their corresponding vanishing points for camera calibration, as the urban traffic scenes are usually man-made and the important lines and signs for driving are typically lying in the Manhattan directions. For “Manhattan world” scenes, where there are plenty of lines lying in Manhattan directions, the lines in the scene are detected automatically, and the clusters corresponding to Manhattan directions are obtained using RANSAC-like methods. For the more general “quasi-Manhattan world” scenes, where only the lines in two directions can be found naturally, while the lines in the other direction are usually detected trivially or even can be hardly detected, we propose a method to estimate the lines in the third direction to improve the vanishing point estimation accuracy. The method proposed is tested on both two types of scenes, and the accuracy and practicability of this method are demonstrated. Furthermore, calibration experiments on both one image and multiple images are conducted, which show that the results can be more accurate when more images are used.
Sponsorship	IEEE Intelligent Transportation Systems Society
Starting Page	3270
Ending Page	3279
Page Count	10
File Size	1889444
File Format	PDF
ISSN	15249050
Volume Number	16
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Calibration Cameras Image segmentation Bayes methods Accuracy Urban areas Mathematical model Parameter estimation urban traffic scene Camera calibration vanishing point Manhattan direction
Content Type	Text
Resource Type	Article
Subject	Automotive Engineering Mechanical Engineering Computer Science Applications

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