Pano2Vid: Automatic Cinematography for Watching 360° Videos

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dc.contributor.authorSu, Yu-Chuanen_US
dc.contributor.authorJayaraman, Dineshen_US
dc.contributor.authorGrauman, Kristenen_US
dc.contributor.editorWilliam Bares and Vineet Gandhi and Quentin Galvane and Remi Ronfarden_US
dc.date.accessioned2017-04-22T17:13:04Z
dc.date.available2017-04-22T17:13:04Z
dc.date.issued2017
dc.description.abstractWe introduce the novel task of Pano2Vid --- automatic cinematography in panoramic 360° videos. Given a 360° video, the goal is to direct an imaginary camera to virtually capture natural-looking normal field-of-view (NFOV) video. By selecting "where to look" within the panorama at each time step, Pano2Vid aims to free both the videographer and the end viewer from the task of determining what to watch. Towards this goal, we first compile a dataset of 360° videos downloaded from the web, together with human-edited NFOV camera trajectories to facilitate evaluation. Next, we propose AutoCam, a data-driven approach to solve the Pano2Vid task. AutoCam leverages NFOV web video to discriminatively identify space-time "glimpses" of interest at each time instant, and then uses dynamic programming to select optimal human-like camera trajectories. Through experimental evaluation on multiple newly defined Pano2Vid performance measures against several baselines, we show that our method successfully produces informative videos that could conceivably have been captured by human videographers.en_US
dc.description.sectionheadersLive-action Cinematography
dc.description.seriesinformationEurographics Workshop on Intelligent Cinematography and Editing
dc.identifier.doi10.2312/wiced.20171071
dc.identifier.isbn978-3-03868-031-4
dc.identifier.issn2411-9733
dc.identifier.pages45-45
dc.identifier.urihttps://doi.org/10.2312/wiced.20171071
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/wiced20171071
dc.publisherThe Eurographics Associationen_US
dc.titlePano2Vid: Automatic Cinematography for Watching 360° Videosen_US
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