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Vision System and Depth Processing for DRC-HUBO : Vision system and depth processing for DRC-HUBO+

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dc.contributor.authorShim, Inwook-
dc.contributor.authorShin, Seunghak-
dc.contributor.authorBok, Yunsu-
dc.contributor.authorJoo, Kyungdon-
dc.contributor.authorChoi, Dong-Geol-
dc.contributor.authorLee, Joon-Young-
dc.contributor.authorPark, Jaesik-
dc.contributor.authorOh, Jun-Ho-
dc.contributor.authorKweon, In So-
dc.date.accessioned2024-05-09T04:14:11Z-
dc.date.available2024-05-09T04:14:11Z-
dc.date.created2024-05-09-
dc.date.created2024-05-09-
dc.date.issued2016-
dc.identifier.citationProceedings - IEEE International Conference on Robotics and Automation, Vol.2016-June, pp.2456-2463-
dc.identifier.issn1050-4729-
dc.identifier.urihttps://hdl.handle.net/10371/201324-
dc.description.abstractThis paper presents a vision system and a depth processing algorithm for DRC-HUBO+, the winner of the DRC finals 2015. Our system is designed to reliably capture 3D information of a scene and objects and to be robust to challenging environment conditions. We also propose a depth-map upsampling method that produces an outliers-free depth map by explicitly handling depth outliers. Our system is suitable for robotic applications in which a robot interacts with the real-world, requiring accurate object detection and pose estimation. We evaluate our depth processing algorithm in comparison with state-of-the-art algorithms on several synthetic and real-world datasets.-
dc.language영어-
dc.publisherIEEE-
dc.titleVision System and Depth Processing for DRC-HUBO-
dc.title.alternativeVision system and depth processing for DRC-HUBO+-
dc.typeArticle-
dc.identifier.doi10.1109/ICRA.2016.7487398-
dc.citation.journaltitleProceedings - IEEE International Conference on Robotics and Automation-
dc.identifier.wosid000389516202019-
dc.identifier.scopusid2-s2.0-84977496131-
dc.citation.endpage2463-
dc.citation.startpage2456-
dc.citation.volume2016-June-
dc.description.isOpenAccessY-
dc.contributor.affiliatedAuthorPark, Jaesik-
dc.type.docTypeConference Paper-
dc.description.journalClass1-
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  • College of Engineering
  • Dept. of Computer Science and Engineering
Research Area Computer Graphics, Computer Vision, Machine Learning, Robotics

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