Research of Correlation Tracking Algorithm Based on the Function of the Minimum Average Absolute Difference

Hui Ying Dong; Qian Liu; Sheng Fu Chen

doi:10.4028/www.scientific.net/AMR.217-218.1769

Paper Titles

Preparation of Dense Ultrafine TiAl Alloys by Spark Plasma Synthesis from Mechanically Activated Powders
p.1747

Feature Selection Based on GA and PNN
p.1753

Analyze on the Mechanical Properties of Stitched Composites
p.1758

Study on the Analysis of Crack Causes and Control Measures of Prestressed Concrete Cylinder Pipe
p.1763

Research of Correlation Tracking Algorithm Based on the Function of the Minimum Average Absolute Difference
p.1769

Delaunay Graph Based Path Planning of Dynamic Obstacle Avoidance Method for Mobile
p.1775

Optimization Design of CTP Imaging Drum Based on ANSYS
p.1781

Cost Estimation of Post-Earthquake Rehabilitation of Industries Based on BP Neural Network
p.1789

An Amperometric Immunosensor Based on a Polyelectrolyte/Nano Gold Particle Layer-by-Layer Assembly Modified Electrode for the Determination of Clenbuterol in Meat
p.1793

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 217-218Research of Correlation Tracking Algorithm Based...

Research of Correlation Tracking Algorithm Based on the Function of the Minimum Average Absolute Difference

Abstract:

A Correlation tracking algorithm based on the function of the minimum average absolute difference is studied. It aims to search the biggest corresponding parts of the minimum average absolute difference in the next frame image using pixel gray values of part of image region as a template to match and solve the target motion parameters. The matching criterion is small computation, simple operation and can reduce the computing time, improve the algorithm running efficiency. The test to track the car running on the road using this tracking algorithm is presented. The experimental result shows that this algorithm can be very good to track the moving car and the magnitude of tracking window deviating from the moving car is very small.

You might also be interested in these eBooks

High Performance Structures and Materials Engineering

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 217-218)

Pages:

1769-1774

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.217-218.1769

Citation:

Cite this paper

Online since:

March 2011

Authors:

Hui Ying Dong, Qian Liu, Sheng Fu Chen

Keywords:

Correlation Tracking, Function of the Minimum Average Absolute Difference, Matching Criterion

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Alan J. Lipton, Hironobu fujiy-oshi, Raju s. Patil. Moving ta-rget classification and tracki-ng from real-time video, IEEE Workshop on Applications of Co-mputer Vision (WACV), Princet on NJ, 1998. 8-14.

DOI: 10.1109/acv.1998.732851

Google Scholar

[2] Traffic control in the visual detection and tracking of information technology research. Chunbo Wang. 2000. 6, Articles Dissertation Database, http: /202. 115. 61. 27: 83.

Google Scholar

[3] Gabriela Castellano. Investiga-tion and application of a comp-lex wavelet transform algorithm for the estimation of optical flow [D]. King's College, Uni-versity of London, 1999. 258-266.

Google Scholar

[4] Christian Heipke. Overview of i-mage matching techniques[EB/OL]. http: /phot. epfl. ch/workshop/ wk-s96/art_3_1. html. 1996-04-29.

Google Scholar

[5] Fengjun Lv Introduction to digital image processing program[M]. Beijing: Tsinghua University Press, 1999. 130-140.

Google Scholar

[6] MA Song-de,. Compute Vision [M]. Beijing: Science Press, 1998. 36-51.

Google Scholar