CineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systems

dc.contributor.authorAchary, Sudheeren_US
dc.contributor.authorMoorthy, K. L. Bhanuen_US
dc.contributor.authorJaved, Asharen_US
dc.contributor.authorShravan, Nikithaen_US
dc.contributor.authorGandhi, Vineeten_US
dc.contributor.authorNamboodiri, Anoop M.en_US
dc.contributor.editorChristie, Marc and Wu, Hui-Yin and Li, Tsai-Yen and Gandhi, Vineeten_US
dc.date.accessioned2020-05-24T13:14:08Z
dc.date.available2020-05-24T13:14:08Z
dc.date.issued2020
dc.description.abstractAutonomous camera systems are often subjected to an optimization operation to smoothen and stabilize the rough trajectory estimates. Most common filtering techniques do reduce the irregularities in data; however, they fail to mimic the behavior of a human cameraman. Global filtering methods modeling human camera operators have been successful; however, they are limited to offline settings. In this paper, we propose two online filtering methods called Cinefilters, which produce smooth camera trajectories that are motivated by cinematographic principles. The first filter (CineConvex) uses a sliding windowbased convex optimization formulation, and the second (CineCNN) is a CNN based encoder-decoder model. We evaluate the proposed filters in two different settings, namely a basketball dataset and a stage performance dataset. Our models outperform previous methods and baselines on quantitative metrics. The CineConvex and CineCNN filters operate at about 250fps and 1000fps, respectively, with a minor latency (half a second), making them apt for a variety of real-time applications.en_US
dc.description.sectionheadersAfternoon Session
dc.description.seriesinformationWorkshop on Intelligent Cinematography and Editing
dc.identifier.doi10.2312/wiced.20201129
dc.identifier.isbn978-3-03868-127-4
dc.identifier.issn2411-9733
dc.identifier.pages27-33
dc.identifier.urihttps://doi.org/10.2312/wiced.20201129
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/wiced20201129
dc.publisherThe Eurographics Associationen_US
dc.titleCineFilter: Unsupervised Filtering for Real Time Autonomous Camera Systemsen_US
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