Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Mehran Maghoumi"'
Autor:
Corey Pittman, Mykola Maslych, Yasmine M. Moolenaar, Joseph J. LaViola, Mehran Maghoumi, Eugene M. Taranta
Publikováno v:
ACM Transactions on Computer-Human Interaction. 28:1-46
We present Machete, a straightforward segmenter one can use to isolate custom gestures in continuous input. Machete uses traditional continuous dynamic programming with a novel dissimilarity measure to align incoming data with gesture class templates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1cb1bde33ade4f9f409158c41f195ce6
https://doi.org/10.1145/3428068
https://doi.org/10.1145/3428068
Autor:
Minh-Quan Le, Joseph J. LaViola, Andrea Giachetti, Andrea D'Eusanio, Hai-Dang Nguyen, Stefano Pini, Minh-Triet Tran, Simone Soso, Deborah Pintani, Marina Monti, Katia Lupinetti, Rita Cucchiara, Franca Giannini, Andrea Ranieri, Alessandro Simoni, Ariel Caputo, Roberto Vezzani, Mehran Maghoumi, Guido Borghi
Publikováno v:
Computers & graphics 99 (2021): 201–211. doi:10.1016/j.cag.2021.07.007
info:cnr-pdr/source/autori:A. Caputo, A. Giachetti, S. Soso, D. Pintani, A. D'Eusanio, S. Pini, G. Borghi, A. Simoni, R. Vezzani, R. Cucchiara, A. Ranieri, F. Giannini, K. Lupinetti, M. Monti, M. Maghoumi, J.J. LaViola Jr, M.-Q. Le, H.-D. Nguyen, M.-T. Tran/titolo:SHREC 2021: Skeleton-based hand gesture recognition in the wild/doi:10.1016%2Fj.cag.2021.07.007/rivista:Computers & graphics/anno:2021/pagina_da:201/pagina_a:211/intervallo_pagine:201–211/volume:99
info:cnr-pdr/source/autori:A. Caputo, A. Giachetti, S. Soso, D. Pintani, A. D'Eusanio, S. Pini, G. Borghi, A. Simoni, R. Vezzani, R. Cucchiara, A. Ranieri, F. Giannini, K. Lupinetti, M. Monti, M. Maghoumi, J.J. LaViola Jr, M.-Q. Le, H.-D. Nguyen, M.-T. Tran/titolo:SHREC 2021: Skeleton-based hand gesture recognition in the wild/doi:10.1016%2Fj.cag.2021.07.007/rivista:Computers & graphics/anno:2021/pagina_da:201/pagina_a:211/intervallo_pagine:201–211/volume:99
Gesture recognition is a fundamental tool to enable novel interaction paradigms in a variety of application scenarios like Mixed Reality environments, touchless public kiosks, entertainment systems, and more. Recognition of hand gestures can be nowad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0fe4abdf624a7ab3cfb7b41365066496
http://hdl.handle.net/11562/1052336
http://hdl.handle.net/11562/1052336
Publikováno v:
IUI
Synthetic data generation to improve classification performance (data augmentation) is a well-studied problem. Recently, generative adversarial networks (GAN) have shown superior image data augmentation performance, but their suitability in gesture s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae2b9950e00f707beea2a6202eb34c57
http://arxiv.org/abs/2011.09149
http://arxiv.org/abs/2011.09149
Autor:
Mykola Maslych, Eugene M. Taranta, Joseph J. LaViola, Corey Pittman, Mehran Maghoumi, Jack P. Oakley
Publikováno v:
CHI
Those who design gesture recognizers and user interfaces often use data collection applications that enable users to comfortably produce gesture training samples. In contrast, games present unique contexts that impact cognitive load and have the pote
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44d492e8afcd33b1a97c2d387a9f66d2
https://doi.org/10.1145/3313831.3376417
https://doi.org/10.1145/3313831.3376417
Autor:
Joseph J. LaViolaJr., Mehran Maghoumi
Publikováno v:
Advances in Visual Computing ISBN: 9783030337193
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52a108fd5a711c1e42b8c95400502185
https://doi.org/10.1007/978-3-030-33720-9_54
https://doi.org/10.1007/978-3-030-33720-9_54
Publikováno v:
ICRA
We introduce an interactive system for extracting the geometries of generalized cylinders and cuboids from single-or multiple-view point clouds. Our proposed method is intuitive and only requires the object's silhouettes to be traced by the user. Lev
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a453c5a2d85bcffaa80f0f18e053a5d9
https://doi.org/10.1109/icra.2018.8460532
https://doi.org/10.1109/icra.2018.8460532
Publikováno v:
VISSOFT
We introduce Code Park, a novel tool for visualizing codebases in a 3D game-like environment. Code Park aims to improve a programmer's understanding of an existing codebase in a manner that is both engaging and intuitive, appealing to novice users su
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21acebe92444e31ed90a84185a453e30
https://doi.org/10.1109/vissoft.2017.10
https://doi.org/10.1109/vissoft.2017.10
Autor:
Mehran Maghoumi, Corey Pittman, Joseph J. LaViola, Pooya Khaloo, Amirreza Samiei, Eugene M. Taranta
Publikováno v:
CHI
Despite decades of research, there is yet no general rapid prototyping recognizer for dynamic gestures that can be trained with few samples, work with continuous data, and achieve high accuracy that is also modality-agnostic. To begin to solve this p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e35dcf8da9f9b9dbc6b8e9cdedfc6854
https://doi.org/10.1145/3025453.3026002
https://doi.org/10.1145/3025453.3026002
Publikováno v:
UIST
Training gesture recognizers with synthetic data generated from real gestures is a well known and powerful technique that can significantly improve recognition accuracy. In this paper we introduce a novel technique called gesture path stochastic resa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f22ad9af07ad84049d6a9b3f6559763
https://doi.org/10.1145/2984511.2984525
https://doi.org/10.1145/2984511.2984525
Autor:
Mehran Maghoumi, Brian J. Ross
Publikováno v:
CIMSIVP
Visual pattern recognition and classification is a challenging computer vision problem. Genetic programming has been applied towards automatic visual pattern recognition. One of the main factors in evolving effective classifiers is the suitability of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3389ad2e91228a368d68ac3a19e3cbf5
https://doi.org/10.1109/cimsivp.2014.7013278
https://doi.org/10.1109/cimsivp.2014.7013278