000134989 001__ 134989
000134989 005__ 20250120150149.0
000134989 0247_ $$2doi$$a10.1109/IROS55552.2023.10342280
000134989 0248_ $$2sideral$$a138488
000134989 037__ $$aART-2023-138488
000134989 041__ $$aeng
000134989 100__ $$aPueyo, Pablo$$uUniversidad de Zaragoza
000134989 245__ $$aCineTransfer: Controlling a Robot to Imitate Cinematographic Style from a Single Example
000134989 260__ $$c2023
000134989 5203_ $$aThis work presents CineTransfer, an algorithmic framework that drives a robot to record a video sequence that mimics the cinematographic style of an input video. We propose features that abstract the aesthetic style of the input video, so the robot can transfer this style to a scene with visual details that are significantly different from the input video. The framework builds upon CineMPC, a tool that allows users to control cinematographic features, like subjects' position on the image and the depth of field, by manipulating the intrinsics and extrinsics of a cinematographic camera. However, CineMPC requires a human expert to specify the desired style of the shot (composition, camera motion, zoom, focus, etc). CineTransfer bridges this gap, aiming a fully autonomous cinematographic platform. The user chooses a single input video as a style guide. CineTransfer extracts and optimizes two important style features, the composition of the subject in the image and the scene depth of field, and provides instructions for CineMPC to control the robot to record an output sequence that matches these features as closely as possible. In contrast with other style transfer methods, our approach is a lightweight and portable framework which does not require deep network training or extensive datasets. Experiments with real and simulated videos demonstrate the system's ability to analyze and transfer style between recordings, and are available in the supplementary video 1 1 https://youtu.be/_QzNz5WUtpk
000134989 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000134989 592__ $$a1.094$$b2023
000134989 593__ $$aComputer Science Applications$$c2023
000134989 593__ $$aSoftware$$c2023
000134989 593__ $$aControl and Systems Engineering$$c2023
000134989 593__ $$aComputer Vision and Pattern Recognition$$c2023
000134989 594__ $$a4.4$$b2023
000134989 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000134989 700__ $$0(orcid)0000-0002-7600-0002$$aMontijano, Eduardo
000134989 700__ $$0(orcid)0000-0001-7853-3622$$aMurillo, Ana C.
000134989 700__ $$aSchwager, Mac
000134989 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000134989 773__ $$g(2023), 10044-10049$$pProc. IEEE/RSJ Int. Conf. Intell. Rob. Syst.$$tProceedings of the ... IEEE/RSJ International Conference on Intelligent Robots and Systems$$x2153-0858
000134989 8564_ $$s3292244$$uhttps://zaguan.unizar.es/record/134989/files/texto_completo.pdf$$yVersión publicada
000134989 8564_ $$s3412974$$uhttps://zaguan.unizar.es/record/134989/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000134989 909CO $$ooai:zaguan.unizar.es:134989$$particulos$$pdriver
000134989 951__ $$a2025-01-20-14:59:53
000134989 980__ $$aARTICLE