Shoot360: Normal View Video Creation from City Panorama Footage
Anyi Rao, Linning Xu, Dahua Lin
Abstract
We present Shoot360, a system that efficiently generates multi-shot normal view videos with desired content presentation and various cinematic styles, given a collection of 360 video recordings on different environments. The core of our system is a three-step decision process: 1) It firstly semantically analyzes the contents of interest from each panorama environment based on shot units, and produces a guidance that specifies the semantic focus and movement type of its output shot according to the user specification on content presentation and cinematic styles. 2) Based on the obtained guidance, it generates video candidates for each shot with shot-level control parameters for view projections following the filming rules. 3) The system further aggregates the projected normal view shots with the imposed local and global constraints, which incorporates the external knowledge learned from exemplar videos and professional filming rules. Extensive experiments verify the effectiveness of our system design, and we conclude with promising extensions for applying it to more generalized scenarios.
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