Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Antoine Manzanera"'
Publikováno v:
IET Computer Vision, Vol 11, Iss 7, Pp 541-549 (2017)
This study presents a spatio‐temporal motion descriptor that is computed from a spatially‐constrained decomposition and applied to online classification and recognition of human activities. The method starts by computing a dense optical flow with
Externí odkaz:
https://doaj.org/article/ebd76e3636274c5b8a40059662911b4e
Autor:
Clément Pinard, Antoine Manzanera
Publikováno v:
Multimedia Tools and Applications.
We present a protocol to construct your own depth validation dataset for navigation. This protocol, called RDC for Rigid Depth Constructor, aims at being more accessible and cheaper than already existing techniques, requiring only a camera and a Lida
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b87b45c37a1db001aae42e6035948e9
https://doi.org/10.1007/s11042-023-14743-0
https://doi.org/10.1007/s11042-023-14743-0
Publikováno v:
Journal of Medical and Biological Engineering. 42:204-215
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7cf865e88213d7cb7eddc28009d71e6
https://doi.org/10.1007/s40846-022-00691-x
https://doi.org/10.1007/s40846-022-00691-x
Publikováno v:
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::040ff51e652205e5b31e169131c42e9e
https://doi.org/10.1109/wacv56688.2023.00132
https://doi.org/10.1109/wacv56688.2023.00132
Autor:
Souhir Khessiba, Ahmed Ghazi Blaiech, Antoine Manzanera, Khaled Ben Khalifa, Asma Ben Abdallah, Mohamed Hédi Bedoui
Publikováno v:
Advances in Computational Collective Intelligence ISBN: 9783031162091
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f299a6631bad9475325175cab8d8155f
https://doi.org/10.1007/978-3-031-16210-7_16
https://doi.org/10.1007/978-3-031-16210-7_16
Publikováno v:
Pattern Recognition and Artificial Intelligence ISBN: 9783031090363
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54859ab175166b6cd2f148f8071a160c
https://doi.org/10.1007/978-3-031-09037-0_55
https://doi.org/10.1007/978-3-031-09037-0_55
Publikováno v:
17th International Symposium on Medical Information Processing and Analysis.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34764517d306b338af99d40c19df6024
https://doi.org/10.1117/12.2606293
https://doi.org/10.1117/12.2606293
Autor:
Jarbas Joaci de Mesquita Sá Junior, Lucas Correia Ribas, Odemir Martinez Bruno, Antoine Manzanera
Publikováno v:
Applied Soft Computing
Applied Soft Computing, Elsevier, 2021
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Applied Soft Computing, Elsevier, 2021
Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual)
Universidade de São Paulo (USP)
instacron:USP
Dynamic textures (DTs) are pseudo periodic data on a space × time support, that can represent many natural phenomena captured from video footages. Their modeling and recognition are useful in many applications of computer vision. This paper presents
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e9ff61d4c5d80ca41ca29cbd74b9bc0
https://hal.archives-ouvertes.fr/hal-03431533
https://hal.archives-ouvertes.fr/hal-03431533
Autor:
Antoine Manzanera, Daniela Pamplona
Publikováno v:
International Conference on Pattern Recognition (ICPR 2020)
International Conference on Pattern Recognition (ICPR 2020), Jan 2021, Milan, Italy
ICPR
International Conference on Pattern Recognition (ICPR 2020), Jan 2021, Milan, Italy
ICPR
International audience; With the rise of big data sets, learning algorithms must be adapted to piece-wise mechanisms to tackle large-scale calculations' time and memory costs. Furthermore, for most learning embedded systems, the input data are fed se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4106a10648060bbc550dd18fa6fad9ae
https://hal.archives-ouvertes.fr/hal-03012909/document
https://hal.archives-ouvertes.fr/hal-03012909/document
Publikováno v:
Journal of Real-Time Image Processing
Journal of Real-Time Image Processing, Springer Verlag, In press, ⟨10.1007/s11554-020-01057-9⟩
Journal of Real-Time Image Processing, Springer Verlag, In press, ⟨10.1007/s11554-020-01057-9⟩
A very low dimension frame-level motion descriptor is herein proposed with the capability to represent incomplete dynamics, thus allowing online action prediction. At each frame, a set of local trajectory kinematic cues are spatially pooled using a c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b8a16a018ad1ece327a079fb6bc62f47
https://hal.archives-ouvertes.fr/hal-03204019
https://hal.archives-ouvertes.fr/hal-03204019