Efficient normalized cross correlation calculation method for stereo vision based robot navigation

Authors:
Yehu Shen
Affiliations:
Department of System Integration and IC Design, Suzhou Institute of Nano-tech and Nano-bionics, Chinese Academy of Sciences, Suzhou, China 215125
Venue:
Frontiers of Computer Science in China
Year:
2011

Citing 12
Cited 0

Building 3-D Human Face Models from Two Photographs

Journal of VLSI Signal Processing Systems - Special issue on multimedia signal processing
A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms

International Journal of Computer Vision
Non-parametric Local Transforms for Computing Visual Correspondence

ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Summed-area tables for texture mapping

SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Advances in Computational Stereo

IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Real-Time Face Detection

International Journal of Computer Vision
The Tyzx DeepSea G2 Vision System, ATaskable, Embedded Stereo Camera

CVPRW '06 Proceedings of the 2006 Conference on Computer Vision and Pattern Recognition Workshop
Stanley: The robot that won the DARPA Grand Challenge: Research Articles

Journal of Robotic Systems - Special Issue on the DARPA Grand Challenge, Part 2
Computer Vision on Mars

International Journal of Computer Vision
Autonomous driving in urban environments: Boss and the Urban Challenge

Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part I
Fast normalized cross correlation for motion tracking using basis functions

Computer Methods and Programs in Biomedicine
Fast variable window for stereo correspondence using integral images

CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition

Quantified Score

Hi-index	0.00

Visualization

Abstract

Stereo vision systems are widely used for autonomous robot navigation. Most of them apply local window based methods for real-time purposes. Normalized cross correlation (NCC) is notorious for its high computational cost, though it is robust to different illumination conditions between two cameras. It is rarely used in real-time stereo vision systems. This paper proposes an efficient normalized cross correlation calculation method based on the integral image technique. Its computational complexity has no relationship to the size of the matching window. Experimental results show that our algorithm can generate the same results as traditional normalized cross correlation with a much lower computational cost. Our algorithm is suitable for planet rover navigation.