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