| Texto completo | |
| Autor(es): Mostrar menos - |
Pinto, Allan
;
Cordova, Manuel A.
;
Decker, Luis G. L.
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Flores-Campana, Jose L.
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Souza, Marcos R.
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dos Santos, Andreza A.
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Conceicao, Jhonatas S.
;
Gagliardi, Henrique F.
;
Luvizon, Diogo C.
;
Torres, Ricardo da S.
;
Pedrini, Helio
;
IEEE
Número total de Autores: 12
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| Tipo de documento: | Artigo Científico |
| Fonte: | 2020 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP); v. N/A, p. 5-pg., 2020-01-01. |
| Resumo | |
Stereo vision is a growing topic in computer vision due to the innumerable opportunities and applications this technology offers for the development of modern solutions, such as virtual and augmented reality applications. To enhance the user's experience in three-dimensional virtual environments, the motion parallax estimation is a promising technique to achieve this objective. In this paper, we propose an algorithm for generating parallax motion effects from a single image, taking advantage of state-of-the-art instance segmentation and depth estimation approaches. This work also presents a comparison against such algorithms to investigate the trade-off between efficiency and quality of the parallax motion effects, taking into consideration a multi-task learning network capable of estimating instance segmentation and depth estimation at once. Experimental results and visual quality assessment indicate that the PyD-Net network (depth estimation) combined with Mask R-CNN or FBNet networks (instance segmentation) can produce parallax motion effects with good visual quality. (AU) | |
| Processo FAPESP: | 19/16253-1 - Desvendando o segredo do futebol Brasileiro e Holandês, capturando elementos de estilo de jogo e estratégias de sucesso |
| Beneficiário: | Allan da Silva Pinto |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |
| Processo FAPESP: | 16/50250-1 - O segredo de jogar futebol: Brasil versus Holanda |
| Beneficiário: | Sergio Augusto Cunha |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |
| Processo FAPESP: | 17/12646-3 - Déjà vu: coerência temporal, espacial e de caracterização de dados heterogêneos para análise e interpretação de integridade |
| Beneficiário: | Anderson de Rezende Rocha |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |