Architectures for stereo vision

authored by

Christian Banz, Holger Blume, Peter Pirsch

Abstract

Stereo vision is an elementary problem for many computer vision tasks. It has been widely studied under the two aspects of increasing the quality of the results and accelerating the computational processes. This chapter provides theoretic background on stereo vision systems and discusses architectures and implementations for real-time applications. In particular, the computationally most intensive part, the stereo matching, is discussed on the example of one of the leading algorithms, the semi-global matching (SGM). For this algorithm two implementations are presented in detail on two of the most relevant platforms for real-time image processing today: Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs). Thus, the major differences in designing parallelization techniques for extremely different image processing platforms are being illustrated.

Organisation(s)

Institute of Microelectronic Systems

Type

Contribution to book/anthology

Pages

483-515

No. of pages

33

Publication date

10.05.2013

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Engineering(all), Computer Science(all)

Electronic version(s)

https://doi.org/10.1007/978-1-4614-6859-2_16 (Access: Closed)