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The paper considers semi-global stereo matching in the context of vision-based driver assistance systems. The need for real-time performance in this field requires a design change of the originally proposed method to run on current hardware. This paper proposes such a new design; the novel strategy first generates a disparity map from half-resolution input images. The result is then used as prior to restrict the disparity search space for full-resolution computation. This approach is compared to an SGM strategy as employed currently in a state-of-the-art real-time FPGA solution. Furthermore, trinocular stereo evaluation is performed on ten real-world traffic sequences with a total of 4,000 trinocular frames. An extension to the original evaluation methodology is proposed to resolve ambiguities and to incorporate disparity density in a statistically meaningful way. Evaluation results indicate that the novel SGM method is up to 40% faster when compared to the previous strategy. It returns denser disparity maps, and is also more accurate on evaluated traffic scenes. | The paper considers semi-global stereo matching in the context of vision-based driver assistance systems. The need for real-time performance in this field requires a design change of the originally proposed method to run on current hardware. This paper proposes such a new design; the novel strategy first generates a disparity map from half-resolution input images. The result is then used as prior to restrict the disparity search space for full-resolution computation. This approach is compared to an SGM strategy as employed currently in a state-of-the-art real-time FPGA solution. Furthermore, trinocular stereo evaluation is performed on ten real-world traffic sequences with a total of 4,000 trinocular frames. An extension to the original evaluation methodology is proposed to resolve ambiguities and to incorporate disparity density in a statistically meaningful way. Evaluation results indicate that the novel SGM method is up to 40% faster when compared to the previous strategy. It returns denser disparity maps, and is also more accurate on evaluated traffic scenes. | ||
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* [https://link.springer.com/content/pdf/10.1007%2F978-3-642-25367-6_35.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-642-25367-6_35.pdf] | * [https://link.springer.com/content/pdf/10.1007%2F978-3-642-25367-6_35.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-642-25367-6_35.pdf] | ||
| − | * [http://link.springer.com/content/pdf/10.1007/978-3-642-25367-6_35 http://link.springer.com/content/pdf/10.1007/978-3-642-25367-6_35],[http://dx.doi.org/10.1007/978-3-642-25367-6_35 http://dx.doi.org/10.1007/978-3-642-25367-6_35] under the license http://www.springer.com/tdm | + | * [http://link.springer.com/content/pdf/10.1007/978-3-642-25367-6_35 http://link.springer.com/content/pdf/10.1007/978-3-642-25367-6_35], |
| + | : [http://dx.doi.org/10.1007/978-3-642-25367-6_35 http://dx.doi.org/10.1007/978-3-642-25367-6_35] under the license http://www.springer.com/tdm | ||
| − | * [https://researchspace.auckland.ac.nz/handle/2292/24784 https://researchspace.auckland.ac.nz/handle/2292/24784],[https://link.springer.com/chapter/10.1007/978-3-642-25367-6_35 https://link.springer.com/chapter/10.1007/978-3-642-25367-6_35],[https:// | + | * [https://researchspace.auckland.ac.nz/handle/2292/24784 https://researchspace.auckland.ac.nz/handle/2292/24784], |
| + | : [https://link.springer.com/chapter/10.1007/978-3-642-25367-6_35 https://link.springer.com/chapter/10.1007/978-3-642-25367-6_35], | ||
| + | : [https://dblp.uni-trier.de/db/conf/psivt/psivt2011-1.html#HermannK11 https://dblp.uni-trier.de/db/conf/psivt/psivt2011-1.html#HermannK11], | ||
| + | : [https://doi.org/10.1007/978-3-642-25367-6_35 https://doi.org/10.1007/978-3-642-25367-6_35], | ||
| + | : [https://www.scipedia.com/public/Hermann_Klette_2011a https://www.scipedia.com/public/Hermann_Klette_2011a], | ||
| + | : [https://academic.microsoft.com/#/detail/1600748096 https://academic.microsoft.com/#/detail/1600748096] | ||
Latest revision as of 16:16, 21 January 2021
Abstract
The paper considers semi-global stereo matching in the context of vision-based driver assistance systems. The need for real-time performance in this field requires a design change of the originally proposed method to run on current hardware. This paper proposes such a new design; the novel strategy first generates a disparity map from half-resolution input images. The result is then used as prior to restrict the disparity search space for full-resolution computation. This approach is compared to an SGM strategy as employed currently in a state-of-the-art real-time FPGA solution. Furthermore, trinocular stereo evaluation is performed on ten real-world traffic sequences with a total of 4,000 trinocular frames. An extension to the original evaluation methodology is proposed to resolve ambiguities and to incorporate disparity density in a statistically meaningful way. Evaluation results indicate that the novel SGM method is up to 40% faster when compared to the previous strategy. It returns denser disparity maps, and is also more accurate on evaluated traffic scenes.
Original document
The different versions of the original document can be found in:
- http://dx.doi.org/10.1007/978-3-642-25367-6_35 under the license http://www.springer.com/tdm
Document information
Published on 01/01/2011
Volume 2011, 2011
DOI: 10.1007/978-3-642-25367-6_35
Licence: CC BY-NC-SA license
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