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This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are comparatively evaluated using real-world vehicle image sequences. | This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are comparatively evaluated using real-world vehicle image sequences. | ||
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* [https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf] | * [https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf] | ||
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| + | * [http://link.springer.com/content/pdf/10.1007/978-3-540-92957-4_53 http://link.springer.com/content/pdf/10.1007/978-3-540-92957-4_53], | ||
| + | : [http://dx.doi.org/10.1007/978-3-540-92957-4_53 http://dx.doi.org/10.1007/978-3-540-92957-4_53] under the license http://www.springer.com/tdm | ||
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| + | * [https://link.springer.com/chapter/10.1007/978-3-540-92957-4_53 https://link.springer.com/chapter/10.1007/978-3-540-92957-4_53], | ||
| + | : [https://researchspace.auckland.ac.nz/handle/2292/3263 https://researchspace.auckland.ac.nz/handle/2292/3263], | ||
| + | : [https://dblp.uni-trier.de/db/conf/psivt/psivt2009.html#KlappsteinVRWK09 https://dblp.uni-trier.de/db/conf/psivt/psivt2009.html#KlappsteinVRWK09], | ||
| + | : [https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf], | ||
| + | : [https://www.scipedia.com/public/Klappstein_et_al_2009a https://www.scipedia.com/public/Klappstein_et_al_2009a], | ||
| + | : [http://dx.doi.org/10.1007/978-3-540-92957-4_53 http://dx.doi.org/10.1007/978-3-540-92957-4_53], | ||
| + | : [https://doi.org/10.1007/978-3-540-92957-4_53 https://doi.org/10.1007/978-3-540-92957-4_53], | ||
| + | : [https://researchspace.auckland.ac.nz/bitstream/2292/3263/2/MItech-TR-22.pdf https://researchspace.auckland.ac.nz/bitstream/2292/3263/2/MItech-TR-22.pdf], | ||
| + | : [https://academic.microsoft.com/#/detail/1690959182 https://academic.microsoft.com/#/detail/1690959182] | ||
Latest revision as of 14:31, 21 January 2021
Abstract
This paper discusses the detection of moving objects (being a crucial part of driver assistance systems) using monocular or stereoscopic computer vision. In both cases, object detection is based on motion analysis of individually tracked image points (optical flow), providing a motion metric which corresponds to the likelihood that the tracked point is moving. Based on this metric, points are segmented into objects by employing a globally optimal graph-cut algorithm. Both approaches are comparatively evaluated using real-world vehicle image sequences.
Original document
The different versions of the original document can be found in:
- http://dx.doi.org/10.1007/978-3-540-92957-4_53 under the license http://www.springer.com/tdm
- https://researchspace.auckland.ac.nz/handle/2292/3263,
- https://dblp.uni-trier.de/db/conf/psivt/psivt2009.html#KlappsteinVRWK09,
- https://link.springer.com/content/pdf/10.1007%2F978-3-540-92957-4_53.pdf,
- https://www.scipedia.com/public/Klappstein_et_al_2009a,
- http://dx.doi.org/10.1007/978-3-540-92957-4_53,
- https://doi.org/10.1007/978-3-540-92957-4_53,
- https://researchspace.auckland.ac.nz/bitstream/2292/3263/2/MItech-TR-22.pdf,
- https://academic.microsoft.com/#/detail/1690959182
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Document information
Published on 01/01/2009
Volume 2009, 2009
DOI: 10.1007/978-3-540-92957-4_53
Licence: CC BY-NC-SA license
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