Abstract
Efficient yet accurate extraction of depth from stereo image pairs is required by systems with low power resources, such as robotics and embedded systems. State-of-the-art stereo matching methods based on convolutional neural networks require intensive computations on GPUs and are difficult to deploy on embedded systems. In this paper, we propose MTStereo2.0, an improved version of the MTStereo stereo matching method, which includes a more robust context-driven cost function, better detection of incorrect matches and the computation of disparity at pixel level. MTStereo provides accurate sparse and semi-dense depth estimation and does not require intensive GPU computations. We tested it on several benchmark data sets, namely KITTI 2015, Driving, FlyingThings3D, Middlebury 2014, Monkaa and the TrimBot2020 garden data sets, and achieved competitive accuracy. The code is available at https://github.com/rbrandt1/MaxTreeS.
Original language | English |
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Title of host publication | Computer Analysis of Images and Patterns - 19th International Conference, CAIP 2021, Proceedings |
Editors | Nicolas Tsapatsoulis, Andreas Panayides, Theo Theocharides, Andreas Lanitis, Andreas Lanitis, Constantinos Pattichis, Constantinos Pattichis, Mario Vento |
Publisher | Springer |
Pages | 110-119 |
Number of pages | 10 |
ISBN (Print) | 9783030891275 |
DOIs | |
Publication status | Published - 31 Oct 2021 |
Event | 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021 - Virtual, Online Duration: 28 Sept 2021 → 30 Sept 2021 Conference number: 19 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13052 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 19th International Conference on Computer Analysis of Images and Patterns, CAIP 2021 |
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Abbreviated title | CAIP 2021 |
City | Virtual, Online |
Period | 28/09/21 → 30/09/21 |
Keywords
- 2022 OA procedure
- Stereo matching
- Max-Tree