Zobrazeno 1 - 10
of 52
pro vyhledávání: '"Afzal Godil"'
Autor:
Afzal Godil, Xiaolan Li
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
This paper investigates the capabilities of the Bag-of-Words (BWs) method in the 3D shape retrieval field. The contributions of this paper are (1) the 3D shape retrieval task is categorized from different points of view: specific versus generic, part
Externí odkaz:
https://doaj.org/article/c51f838a909b4611a48268bea85e2bb9
Autor:
Jon Fiscus, Jesse Zhang, Andrew Delgado, Jim Golden, Baptiste Chocot, Yooyoung Lee, Afzal Godil, Eliot Godard, Lukas Diduch
Publikováno v:
WACV (Workshops)
This paper presents a summary and results for the ActEV’20 SDL (Activities in Extended Video Sequestered Data Leaderboard) challenge that was held under the CVPR’20 ActivityNet workshop [38]. The primary goal of the challenge was to provide an im
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed191845dc2735bc445e360e3e418a88
https://doi.org/10.1109/wacvw52041.2021.00010
https://doi.org/10.1109/wacvw52041.2021.00010
Autor:
Yooyoung Lee, Lukas Diduch, Jim Golden, Jon Fiscus, Maxime Hubert, Andrew Delgado, Afzal Godil
Publikováno v:
WACV Workshops
Despite previous data collection efforts and benchmark studies, progress in activity detection technologies has been slow, especially with applications that meet practical needs for the video analytics domain. In this paper, we discuss the results fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::df90d31aa654e83983289552c0b735d0
https://doi.org/10.1109/wacvw50321.2020.9096926
https://doi.org/10.1109/wacvw50321.2020.9096926
Publikováno v:
WACV Workshops
Video analytic technologies that are able to detect and classify activity are crucial for applications in many domains, such as transportation and public safety. In spite of many data collection efforts and benchmark studies in the computer vision co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cc681bf74936df92c27bcd287e33449
https://doi.org/10.1109/wacvw.2019.00008
https://doi.org/10.1109/wacvw.2019.00008
Publikováno v:
Multimedia Tools and Applications. 72:1531-1560
Non-rigid and partial 3D model retrieval are two significant and challenging research directions in the field of 3D model retrieval. Little work has been done in proposing a hybrid shape descriptor that works for both retrieval scenarios, let alone t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f47b18a560297cbcbcff5e683267cfc2
https://doi.org/10.1007/s11042-013-1464-2
https://doi.org/10.1007/s11042-013-1464-2
Publikováno v:
Machine Vision and Applications. 24:1685-1704
Content-based 3D object retrieval has become an active topic in many research communities. In this paper, we propose a novel visual similarity-based 3D shape retrieval method (CM-BOF) using Clock Matching and Bag-of-Features. Specifically, pose norma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8446a7b55e7478a959941c1e929e7040
https://doi.org/10.1007/s00138-013-0501-5
https://doi.org/10.1007/s00138-013-0501-5
Autor:
Gary K. L. Tam, Sheng Cheng, Chunyuan Li, Atsushi Tatsuma, Zhouhui Lian, Yijuan Lu, Bo Li, Henry Johan, L. Lai, Andrea Giachetti, Valeria Garro, Umberto Castellani, Zhi-Quan Cheng, Junwei Han, Paul L. Rosin, Afzal Godil, David Pickup, Michael M. Bronstein, Roee Litman, Shuhui Bu, A. Ben Hamza, Jianbo Ye, Luca Isaia, Masaki Aono, X. Liu, Haisheng Li, L. Sun, Z. Liu, Xianfang Sun, Alexander M. Bronstein, Ralph R. Martin
Publikováno v:
International Journal of Computer Vision 120 (2016): 169–193. doi:10.1007/s11263-016-0903-8
info:cnr-pdr/source/autori:Pickup D.; Sun X.; Rosin P.L.; Martin R.R.; Cheng Z.; Lian Z.; Aono M.; Hamza A.B.; Bronstein A.; Bronstein M.; Bu S.; Castellani U.; Cheng S.; Garro V.; Giachetti A.; Godil A.; Isaia L.; Han J.; Johan H.; Lai L.; Li B.; Li C.; Li H.; Litman R.; Liu X.; Liu Z.; Lu Y.; Sun L.; Tam G.; Tatsuma A.; Ye J./titolo:Shape Retrieval of Non-rigid 3D Human Models/doi:10.1007%2Fs11263-016-0903-8/rivista:International Journal of Computer Vision/anno:2016/pagina_da:169/pagina_a:193/intervallo_pagine:169–193/volume:120
info:cnr-pdr/source/autori:Pickup D.; Sun X.; Rosin P.L.; Martin R.R.; Cheng Z.; Lian Z.; Aono M.; Hamza A.B.; Bronstein A.; Bronstein M.; Bu S.; Castellani U.; Cheng S.; Garro V.; Giachetti A.; Godil A.; Isaia L.; Han J.; Johan H.; Lai L.; Li B.; Li C.; Li H.; Litman R.; Liu X.; Liu Z.; Lu Y.; Sun L.; Tam G.; Tatsuma A.; Ye J./titolo:Shape Retrieval of Non-rigid 3D Human Models/doi:10.1007%2Fs11263-016-0903-8/rivista:International Journal of Computer Vision/anno:2016/pagina_da:169/pagina_a:193/intervallo_pagine:169–193/volume:120
3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. We extend our recent paper which provided a benchmark for testing non-rigid 3D s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e0eac7a71dc6317d2321969a06c94ab1
https://publica.fraunhofer.de/handle/publica/246998
https://publica.fraunhofer.de/handle/publica/246998
Autor:
Masaki Aono, Atsushi Tatsuma, Chunyuan Li, Valeria Garro, Silvia Biasotti, M. Spagnuolo, A. Ben Hamza, Afzal Godil, Andrea Cerri, Chika Sanada, Andrea Giachetti, Santiago Velasco-Forero, Daniela Giorgi
Publikováno v:
The visual computer 32 (2016): 217–241. doi:10.1007/s00371-015-1146-3
The Visual Computer
The Visual Computer, 2015, 32 (2), pp.217-241. ⟨10.1007/s00371-015-1146-3⟩
info:cnr-pdr/source/autori:Biasotti S.M.; Cerri A.; Aono M.; Hamza A.B.; Garro V.; Giachetti A.; Giorgi D.; Godil A.A.; Li G.C.; Sanada C.; Spagnuolo M.; Tatsuma A.; Velasco Forero S./titolo:Retrieval and classification methods for textured 3D models: a comparative study/doi:10.1007%2Fs00371-015-1146-3/rivista:The visual computer/anno:2016/pagina_da:217/pagina_a:241/intervallo_pagine:217–241/volume:32
The Visual Computer, Springer Verlag, 2015, 32 (2), pp.217-241. ⟨10.1007/s00371-015-1146-3⟩
The Visual Computer
The Visual Computer, 2015, 32 (2), pp.217-241. ⟨10.1007/s00371-015-1146-3⟩
info:cnr-pdr/source/autori:Biasotti S.M.; Cerri A.; Aono M.; Hamza A.B.; Garro V.; Giachetti A.; Giorgi D.; Godil A.A.; Li G.C.; Sanada C.; Spagnuolo M.; Tatsuma A.; Velasco Forero S./titolo:Retrieval and classification methods for textured 3D models: a comparative study/doi:10.1007%2Fs00371-015-1146-3/rivista:The visual computer/anno:2016/pagina_da:217/pagina_a:241/intervallo_pagine:217–241/volume:32
The Visual Computer, Springer Verlag, 2015, 32 (2), pp.217-241. ⟨10.1007/s00371-015-1146-3⟩
International audience; This paper presents a comparative study of six methods for the retrieval and classification of tex-tured 3D models, which have been selected as representative of the state of the art. To better analyse and control how methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db117bd322d23e07b839ad5bcaba6f4b
https://openportal.isti.cnr.it/doc?id=people______::6c29dca9204102ae9cb700744bcc8e64
https://openportal.isti.cnr.it/doc?id=people______::6c29dca9204102ae9cb700744bcc8e64
Publikováno v:
The Visual Computer. 28:901-917
In this paper, we present an evaluation strategy based on human-generated ground truth to measure the performance of 3D interest point detection techniques. We provide quantitative evaluation measures that relate automatically detected interest point
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8098ddfb7fa6f326fefc8ce5cc961e7
https://doi.org/10.1007/s00371-012-0746-4
https://doi.org/10.1007/s00371-012-0746-4