World Library  

QR link for Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data : Volume Ii-3/W2, Issue 1 (02/10/2013)
Add to Book Shelf
Flag as Inappropriate
Email this Book

Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data : Volume Ii-3/W2, Issue 1 (02/10/2013)

By Choi, K.

Click here to view

Book Id: WPLBN0004013816
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data : Volume Ii-3/W2, Issue 1 (02/10/2013)  
Author: Choi, K.
Volume: Vol. II-3/W2, Issue 1
Language: English
Subject: Science, Isprs, Annals
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Historic
Publication Date:
2013
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications

Citation

APA MLA Chicago

Lee, I., Tanathong, S., Kim, H., & Choi, K. (2013). Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data : Volume Ii-3/W2, Issue 1 (02/10/2013). Retrieved from http://community.worldlibrary.net/


Description
Description: Dept. of Geoinformatics, The University of Seoul, 163 Seoulsiripdaero, Dongdaemun-gu, Seoul 130-743, Korea. Recently, a car employs various built-in sensors such as a speedometer, odometer, accelerometer and angular rate sensor for safety and maintenance. These sensory data can be provided in real time through a CAN (Controller Area Network) bus. In addition, image sequences can be provided from various cameras mounted to the car, such as built-in front and around view monitoring cameras. We thus propose an image based car navigation framework to determine car position and attitude using the built-in sensory data such as a speed, angular rate and images from a front view camera. First, we determine the two-dimensional position and attitude of a car using the velocity and angular rate provided in real-time through the CAN bus. We then estimate the three-dimensional position and attitude by conducting sequential bundle block adjustment using the two-dimensional position and attitude and tie points between image sequences. The sequential bundle adjustment can produce accurate results comparable to those from the conventional simultaneous bundle adjustment in real time. As the input to this process, it needs reliable tie points between adjacent images acquired from a real-time image matching process. Hence, we develop an image matching process based on the enhanced KLT algorithm using preliminary exterior orientation parameters. We also construct a test system that can acquire and store built-in sensory data and front camera images at the same time, and conduct experiments with the real data acquired by the system. The experimental results show that the proposed image matching process can generate accurate tie-points with about 0.2 second in average at each epoch. It can successfully meet the requirements from real-time bundle adjustment for image based car navigation.

Summary
Realtime Image Matching for Vision Based Car Navigation with Built-in Sensory Data

 

Click To View

Additional Books


  • 3D Digitization and Mapping of Heritage ... (by )
  • Prediction of Individual's Movement Base... (by )
  • The Attribute Accuracy Assessment of Lan... (by )
  • Comparative Study of Two Automatic Regis... (by )
  • Advanced Dtm Generation from Very High R... (by )
  • Addressing Grand Challenges in Earth Obs... (by )
  • Analysis of the Spatiotemporal Character... (by )
  • Documenting Modern Mexican Architectural... (by )
  • The Impact of Varying Statutory Arrangem... (by )
  • Automatic Extraction of Insulators from ... (by )
  • Analysis of Point Cloud Generation from ... (by )
  • Modelling the Constraints of Spatial Env... (by )
Scroll Left
Scroll Right

 



Copyright © World Library Foundation. All rights reserved. eBooks from World Library are sponsored by the World Library Foundation,
a 501c(4) Member's Support Non-Profit Organization, and is NOT affiliated with any governmental agency or department.