Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Giampaolo Pagnutti"'
Publikováno v:
IET Computer Vision, Vol 11, Iss 8, Pp 633-642 (2017)
We present an approach for segmentation and semantic labelling of RGBD data exploiting together geometrical cues and deep learning techniques. An initial over‐segmentation is performed using spectral clustering and a set of non‐uniform rational B
Externí odkaz:
https://doaj.org/article/1e6fc1a549a4469fab5bbf65ad453312
Publikováno v:
ICDSC
Among the various segmentation techniques, a widely used family of approaches are the ones based on region merging, where an initial oversegmentation is progressively refined by joining segments with similar characteristics. Instead of using determin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c882ba7bb96173a3e095778a9891b48d
https://doi.org/10.1145/3349801.3349810
https://doi.org/10.1145/3349801.3349810
Autor:
Giampaolo Pagnutti, Pietro Zanuttigh
Publikováno v:
Image and Vision Computing. 70:21-31
This paper proposes a segmentation scheme based on the joint usage of color and depth data together with a 3D surface estimation scheme. Firstly a set of multi-dimensional vectors is built from color, geometry and surface orientation information. Nor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9c45e7370ce99d14c4055365f63953ff
https://doi.org/10.1016/j.imavis.2017.12.004
https://doi.org/10.1016/j.imavis.2017.12.004
Publikováno v:
IET Computer Vision. 11:633-642
We present an approach for segmentation and semantic labelling of RGBD data exploiting together geometrical cues and deep learning techniques. An initial over-segmentation is performed using spectral clustering and a set of non-uniform rational B-spl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::56581861fffec61b3c95e6d8958c8f67
https://doi.org/10.1049/iet-cvi.2016.0502
https://doi.org/10.1049/iet-cvi.2016.0502
Publikováno v:
VISIGRAPP (5: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cffe707e13f412eeb904106f65b1b485
http://hdl.handle.net/11577/3276278
http://hdl.handle.net/11577/3276278
Autor:
Pietro Zanuttigh, Giampaolo Pagnutti
Publikováno v:
VISIGRAPP (4: VISAPP)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95881fc6e7d8494d81437fa9d0948a67
https://doi.org/10.5220/0005672700930100
https://doi.org/10.5220/0005672700930100
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319494081
ECCV Workshops (3)
ECCV Workshops (3)
This paper proposes a joint color and depth segmentation scheme exploiting together geometrical clues and a learning stage. The approach starts from an initial over-segmentation based on spectral clustering. The input data is also fed to a Convolutio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4080244798b34875c69e3cfc3ae6a9f
http://hdl.handle.net/11577/3214799
http://hdl.handle.net/11577/3214799
Autor:
Pietro Zanuttigh, Giampaolo Pagnutti
Publikováno v:
ICIP
Scene segmentation is a very challenging problem for which color information alone is often not sufficient. Recently the introduction of consumer depth cameras has opened the way to novel approaches exploiting depth data. This paper proposes a novel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb46e86442c498a6c7a1335f50d1abf0
http://hdl.handle.net/11577/3111121
http://hdl.handle.net/11577/3111121