Cart (Loading....) | Create Account
Close category search window
 

Vision-Based Autonomous Vehicle Guidance for Indoor Security Patrolling by a SIFT-Based Vehicle-Localization Technique

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kuan-Chieh Chen ; Inst. of Multimedia Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan ; Wen-Hsiang Tsai

A novel method for guidance of vision-based autonomous vehicles for indoor security patrolling using scale-invariant feature transformation (SIFT) and vehicle localization techniques is proposed. Along-path objects to be monitored are used as landmarks for vehicle localization. The localization work is accomplished by three steps: SIFT-based object image feature matching, 2-D affine transformation using the Hough transform, and analytic 3-D space transformation. Object monitoring can be simultaneously achieved during the vehicle-localization process, and most planar-surfaced objects can be utilized in the process, greatly enhancing the applicability of the proposed method. Vehicle trajectory deviations from the planned path due to mechanic error accumulation are also estimated by setting up a calibration line on the monitored object image and applying the 3-D space transformation. Moreover, a path-correction technique is proposed to conduct a path adjustment and guide the vehicle to navigate to the next path node. Analysis of the accuracy of the vehicle-localization and path-correction results is finally included. The experimental results show that the proposed method, utilizing only a single view of each object, can guide the vehicle to navigate accurately and monitor objects successfully.

Published in:

Vehicular Technology, IEEE Transactions on  (Volume:59 ,  Issue: 7 )

Date of Publication:

Sept. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.