Translational Motion Estimation of Moving Object Based on Windowed Phase Correlation Algorithm with Kernel Regression

Author

Yu, Yinghuai ; Zhao, Hongda ; Liu, Hong ; Liu, Benyong

Author_Institution

Coll. of Comput. Sci. & Inf. Technol., Guizhou Univ., Guiyang, China

fYear

2010

fDate

21-23 Oct. 2010

Firstpage

1

Lastpage

5

Abstract

Motion estimation is one of the basic problems in digital video processing; it is significant in the applications of video image compression, registration, mosaic, and target detection, and so on. In the base of discussing basic phase correlation algorithm, a method based on kernel regression for constructing two-dimensional circular symmetry window function has been introduced, and the improved scheme based on windowed preprocessing, is proposed for translational motion estimation of moving object. Experimental results show the feasibility of the presented scheme.

Keywords

correlation methods; motion estimation; object detection; regression analysis; video signal processing; basic phase correlation algorithm; digital video processing; kernel regression; moving object estimation; translational motion estimation; two-dimensional circular symmetry window function; windowed phase correlation algorithm; Correlation; Educational institutions; Fitting; Image processing; Kernel; Motion estimation; Nickel;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition (CCPR), 2010 Chinese Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4244-7209-3

Electronic_ISBN

978-1-4244-7210-9

Type

conf

DOI

10.1109/CCPR.2010.5659146

Filename

5659146