Publication
Swifter: Improved Online Video Scrubbing
AbstractOnline streaming video systems have become extremely popular, yet navigating to target scenes of interest can be a challenge. While recent techniques have been introduced to enable real-time seeking, they break down for large videos, where scrubbing the timeline causes video frames to skip and flash too quickly to be comprehendible. We present Swifter, a new video scrubbing technique that displays a grid of pre-cached thumbnails during scrubbing actions. In a series of studies, we first investigate possible design variations of the Swifter technique, and the impact of those variations on its performance. Guided by these results we compare an implementation of Swifter to the previously published Swift technique, in addition to the approaches utilized by YouTube and Netfilx. Our study finds that Swifter significantly outperforms each of these techniques in a scene locating task, by a factor of up to 48%.
Download publicationRelated Resources
See what’s new.
2023
Explore the Industrialization of Construction at AU 2023Learn more about the digital transformation in building and…
2023
Tesseract: Querying Spatial Design Recordings by Manipulating Worlds in MiniatureNew immersive 3D design tools enable the creation of spatial design…
2014
Corticomotor Excitability of Arm Muscles Modulates According to Static Position and Orientation of the Upper LimbOBJECTIVE: We investigated how multi-joint changes in upper limb…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us