Document Type
Pre-Print
Publication Date
2019
Subjects
Computing methodologies, Image manipulation
Abstract
Three-hundred-sixty-degree (360°) video provides an immersive experience for viewers, allowing them to freely explore the world by turning their head. However, creating high-quality 360° video content can be challenging, as viewers may miss important events by looking in the wrong direction, or they may see things that ruin the immersion, such as stitching artifacts and the film crew. We take advantage of the fact that not all directions are equally likely to be observed; most viewers are more likely to see content located at “true north,” i.e., in front of them, due to ergonomic constraints. We therefore propose 360° video direction, where the video is jointly optimized to orient important events to the front of the viewer and visual clutter behind them, while producing smooth camera motion. Unlike traditional video, viewers can still explore the space as desired, but with the knowledge that the most important content is likely to be in front of them. Constraints can be user guided, either added directly on the equirectangular projection or by recording “guidance” viewing directions while watching the video in a VR headset or automatically computed, such as via visual saliency or forward-motion direction. To accomplish this, we propose a new motion estimation technique specifically designed for 360° video that outperforms the commonly used five-point algorithm on wide-angle video. We additionally formulate the direction problem as an optimization where a novel parametrization of spherical warping allows us to correct for some degree of parallax effects. We compare our approach to recent methods that address stabilization-only and converting 360° video to narrow field-of-view video. Our pipeline can also enable the viewing of wide-angle non-360° footage in a spherical 360° space, giving an immersive “virtual cinema” experience for a wide range of existing content filmed with first-person cameras.
Locate the Document
DOI
10.1145/3211889
Persistent Identifier
https://archives.pdx.edu/ds/psu/30137
Citation Details
Tang, Chengzhou; Wang, Oliver; Liu, Feng; and Tan, Ping, "Joint Stabilization and Direction of 360° Videos" (2019). Computer Science Faculty Publications and Presentations. 204.
https://archives.pdx.edu/ds/psu/30137
Description
This is the author’s version of a work. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document.