Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Vu-Lam Nguyen"'
Publikováno v:
IET Computer Vision, Vol 12, Iss 5, Pp 735-743 (2018)
Here, the authors introduce a novel system which incorporates the discriminative motion of oriented magnitude patterns (MOMP) descriptor into simple yet efficient techniques. The authors’ descriptor both investigates the relations of the local grad
Externí odkaz:
https://doaj.org/article/6a5e1d83459b4372a40434c483d28815
Publikováno v:
Multimedia Tools and Applications
Multimedia Tools and Applications, Springer Verlag, In press, ⟨10.1007/s11042-017-4824-5⟩
Multimedia Tools and Applications, Springer Verlag, In press, ⟨10.1007/s11042-017-4824-5⟩
International audience; In this paper, we propose a micro-macro feature combination approach for texture classification. The two disparate yet complementary categories of features are combined. By this way, Local Binary Pattern (LBP) plays the role o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94b5242f33ad9edaa642b879ade0c85d
https://hal.archives-ouvertes.fr/hal-01593393
https://hal.archives-ouvertes.fr/hal-01593393
Publikováno v:
International Symposium on Visual Computing
International Symposium on Visual Computing, Dec 2016, Las Vegas, United States. ⟨10.1007/978-3-319-50832-0_17⟩
Advances in Visual Computing ISBN: 9783319508313
ISVC (2)
International Symposium on Visual Computing, Dec 2016, Las Vegas, United States. ⟨10.1007/978-3-319-50832-0_17⟩
Advances in Visual Computing ISBN: 9783319508313
ISVC (2)
International audience; In this paper, we present a novel descriptor for human action recognition, called Motion of Oriented Magnitudes Patterns (MOMP), which considers the relationships between the local gradient distributions of neighboring patches
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::95c167c72a8214f6f5ddc46314c75df4
https://hal.archives-ouvertes.fr/hal-02265245/document
https://hal.archives-ouvertes.fr/hal-02265245/document
Publikováno v:
2016 23rd International Conference on Pattern Recognition (ICPR)
23rd IEEE International Conference on Pattern Recognition (ICPR 2016)
23rd IEEE International Conference on Pattern Recognition (ICPR 2016), Dec 2016, Cancun, Mexico. ⟨10.1109/ICPR.2016.7899931⟩
ICPR
23rd IEEE International Conference on Pattern Recognition (ICPR 2016)
23rd IEEE International Conference on Pattern Recognition (ICPR 2016), Dec 2016, Cancun, Mexico. ⟨10.1109/ICPR.2016.7899931⟩
ICPR
International audience; Regarding texture features, Local-based methods such as Local Binary Pattern (LBP) and its variants are computationally efficient high-performing but sensitive to noise, and suffering global structure information loss. By cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f485408a9ee6873bfc65960c39e511bd
https://hal.archives-ouvertes.fr/hal-01593389
https://hal.archives-ouvertes.fr/hal-01593389
Akademický článek
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Publikováno v:
CBMI
2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)
International Workshop on Content-based Multimedia Indexing
International Workshop on Content-based Multimedia Indexing, Jun 2016, Bucharest, Romania. ⟨10.1109/CBMI.2016.7500238⟩
2016 14th International Workshop on Content-Based Multimedia Indexing (CBMI)
International Workshop on Content-based Multimedia Indexing
International Workshop on Content-based Multimedia Indexing, Jun 2016, Bucharest, Romania. ⟨10.1109/CBMI.2016.7500238⟩
International audience; In this paper, we propose a combined feature approach which takes full advantages of local structure information and the more global one for improving texture image classification results. In this way, Local Binary Pattern is