Details
| Original language | English |
|---|---|
| Title of host publication | Handbook of Signal Processing Systems |
| Publisher | Springer New York |
| Pages | 483-515 |
| Number of pages | 33 |
| Edition | Second Edition |
| ISBN (electronic) | 9781461468592 |
| ISBN (print) | 9781461468585 |
| Publication status | Published - 10 May 2013 |
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.
ASJC Scopus subject areas
- Engineering(all)
- General Engineering
- Computer Science(all)
- General Computer Science
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Handbook of Signal Processing Systems. Second Edition. ed. Springer New York, 2013. p. 483-515.
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Architectures for stereo vision
AU - Banz, Christian
AU - Blume, Holger
AU - Pirsch, Peter
PY - 2013/5/10
Y1 - 2013/5/10
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85026323241&partnerID=8YFLogxK
U2 - 10.1007/978-1-4614-6859-2_16
DO - 10.1007/978-1-4614-6859-2_16
M3 - Contribution to book/anthology
AN - SCOPUS:85026323241
SN - 9781461468585
SP - 483
EP - 515
BT - Handbook of Signal Processing Systems
PB - Springer New York
ER -