Abstract
Omnidirectional (\(360^\circ \)) video is a novel media format, rapidly becoming adopted in media production and consumption as part of today’s ongoing virtual reality revolution. The goal of automatic camera path generation is to calculate automatically a visually interesting camera path from a \(360^\circ \) video in order to provide a traditional, TV-like consumption experience. In this work, we describe our algorithm for automatic camera path generation, based on extraction of the information of the scene objects with deep learning based methods.
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