Optimization for image stereo-matching using deep reinforcement learning in rule constraints and par...
Optimization for image stereo-matching using deep reinforcement learning in rule constraints and parallax estimation
About this item
Full title
Author / Creator
Ren, Jie , Guan, Fuyu , Li, Xueyan , Cao, Jie and Li, Xiaofeng
Publisher
London: Springer London
Journal title
Language
English
Formats
Publication information
Publisher
London: Springer London
Subjects
More information
Scope and Contents
Contents
Stereo-matching is a hot topic in the field of visual image research, to address the low image-matching accuracy of traditional algorithms. In this paper, an optimization for image stereo-matching algorithm using deep reinforcement learning (DRL) is proposed in rule constraints and parallax estimation. First, the image edge pixel constraint rules a...
Alternative Titles
Full title
Optimization for image stereo-matching using deep reinforcement learning in rule constraints and parallax estimation
Authors, Artists and Contributors
Author / Creator
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2890538456
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2890538456
Other Identifiers
ISSN
0941-0643
E-ISSN
1433-3058
DOI
10.1007/s00521-023-08227-3
