000062988 001__ 62988
000062988 005__ 20190709135427.0
000062988 0247_ $$2doi$$a10.1111/cgf.13086
000062988 0248_ $$2sideral$$a99252
000062988 037__ $$aART-2017-99252
000062988 041__ $$aeng
000062988 100__ $$0(orcid)0000-0002-7796-3177$$aSerrano, Ana$$uUniversidad de Zaragoza
000062988 245__ $$aConvolutional Sparse Coding for Capturing High-Speed Video Content
000062988 260__ $$c2017
000062988 5060_ $$aAccess copy available to the general public$$fUnrestricted
000062988 5203_ $$aVideo capture is limited by the trade-off between spatial and temporal resolution: when capturing videos of high temporal resolution, the spatial resolution decreases due to bandwidth limitations in the capture system. Achieving both high spatial and temporal resolution is only possible with highly specialized and very expensive hardware, and even then the same basic trade-off remains. The recent introduction of compressive sensing and sparse reconstruction techniques allows for the capture of single-shot high-speed video, by coding the temporal information in a single frame, and then reconstructing the full video sequence from this single-coded image and a trained dictionary of image patches. In this paper, we first analyse this approach, and find insights that help improve the quality of the reconstructed videos. We then introduce a novel technique, based on convolutional sparse coding (CSC), and show how it outperforms the state-of-the-art, patch-based approach in terms of flexibility and efficiency, due to the convolutional nature of its filter banks. The key idea for CSC high-speed video acquisition is extending the basic formulation by imposing an additional constraint in the temporal dimension, which enforces sparsity of the first-order derivatives over time.
000062988 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/IMAGER-TIN2016-79710-P$$9info:eu-repo/grantAgreement/ES/MINECO/BLINK$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 682080-CHAMELEON$$9info:eu-repo/grantAgreement/EC/H2020/682080/EU/Intuitive editing of visual appearance from real-world datasets/CHAMELEON$$9info:eu-repo/grantAgreement/ES/MINECO/Lightslice
000062988 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000062988 590__ $$a2.046$$b2017
000062988 591__ $$aCOMPUTER SCIENCE, SOFTWARE ENGINEERING$$b22 / 104 = 0.212$$c2017$$dQ1$$eT1
000062988 592__ $$a0.597$$b2017
000062988 593__ $$aComputer Networks and Communications$$c2017$$dQ1
000062988 593__ $$aComputer Graphics and Computer-Aided Design$$c2017$$dQ2
000062988 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000062988 700__ $$0(orcid)0000-0003-3509-8485$$aGarces, Elena
000062988 700__ $$0(orcid)0000-0003-0060-7278$$aMasia, Belen$$uUniversidad de Zaragoza
000062988 700__ $$0(orcid)0000-0002-7503-7022$$aGutierrez, Diego$$uUniversidad de Zaragoza
000062988 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000062988 773__ $$g36, 8 (2017), 380-389$$pComput. graph. forum$$tCOMPUTER GRAPHICS FORUM$$x0167-7055
000062988 8564_ $$s5705159$$uhttps://zaguan.unizar.es/record/62988/files/texto_completo.pdf$$yVersión publicada
000062988 8564_ $$s93707$$uhttps://zaguan.unizar.es/record/62988/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000062988 909CO $$ooai:zaguan.unizar.es:62988$$particulos$$pdriver
000062988 951__ $$a2019-07-09-11:29:54
000062988 980__ $$aARTICLE