Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Jaesik Park"'
We propose deep virtual markers, a framework for estimating dense and accurate positional information for various types of 3D data. We design a concept and construct a framework that maps 3D points of 3D articulated models, like humans, into virtual
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::61d5bf5fdd3be6ab0c2e48d925c71ed1
Point cloud registration is the task of estimating the rigid transformation that aligns a pair of point cloud fragments. We present an efficient and robust framework for pairwise registration of real-world 3D scans, leveraging Hough voting in the 6D
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0bbfdb8b8da55cc02c3cef968faf853e
Autor:
Kyungdon Joo, Jaesik Park, Seunghak Shin, Joon-Young Lee, Dong-Geol Choi, Jun-Ho Oh, In So Kweon, Yunsu Bok, Inwook Shim
Publikováno v:
ICRA
This 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 robust to challenging environment conditions. We a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62eaa6ea96270cbe25f7f4a8eb5a0646