Extracting Regular FOV Shots from 360 Event Footage
Anh Truonga, Sara Chenb, Ersin Yumerc, David Salesind, Wilmot Lie
- aAdobe Research, San Francisco, CA, USA
- bDurham University, Durham, England, United Kingdom
- cAdobe Research, San Jose, CA, USA
- dSnap Research, Venice, CA, USA
- eAdobe Research, Seattle, WA, USA
Papers open inside SciRah from the original publisher or repository; SciRah never hosts them.
Abstract
Video summaries are a popular way to share important events, but creating good summaries is hard. It requires expertise in both capturing and editing footage. While hiring a professional videographer is possible, this is too costly for most casual events. An alternative is to place 360 video cameras around an event space to capture footage passively and then extract regular field-of-view (RFOV) shots for the summary. This paper focuses on the problem of extracting such RFOV shots. Since we cannot actively control the cameras or the scene, it is hard to create "ideal' shots that adhere strictly to traditional cinematography rules. To better understand the tradeoffs, we study human preferences for static and moving camera RFOV shots generated from 360 footage. From the findings, we derive design guidelines. As a secondary contribution, we use these guidelines to develop automatic algorithms that we demonstrate in a prototype user interface for extracting RFOV shots from 360 videos.
TL;DRThis paper studies human preferences for static and moving camera RFOV shots generated from 360 footage, and derives design guidelines that are used to develop automatic algorithms that are demonstrated in a prototype user interface for extracting RFOv shots from 360 videos. (Semantic Scholar)