Phase-correlation guided search for realtime stereo vision Conference Paper

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Overview

abstract

• In this paper, we propose a new theoretical framework, which is based on phase-correlation, for efficiently solving the correspondence problem. The proposed method allows area matching algorithms to perform at high frame rates, and can be applied to various problems in computer vision. In particular, we demonstrate the advantages of this method in the estimation of dense disparity maps in real time. A fairly optimized version of the proposed algorithm, implemented on a dual-core PC architecture, is capable of running at 100 frames per second with an image size of 256 × 256. © Springer-Verlag Berlin Heidelberg 2009.

authors

• Alba Cadena Francisco Alfonso
• Arce Santana Edgar Román

publication date

• 2009-01-01

published in

• Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)  Journal

Research

keywords

• Area matching; Phase correlation; Real time; Stereo vision Area matching; Correspondence problems; Dense disparity maps; Dual-core; Frames per seconds; Guided search; High frame rate; Image sizes; PC architecture; Phase correlation; Real time; Real time stereo; Theoretical framework; Algorithms; Computer vision; Image matching; Stereo vision

Identity

Digital Object Identifier (DOI)

• 10.1007/978-3-642-10210-3_17

Additional Document Info

start page

• 212

end page

• 223

volume

• 5852 LNCS