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.
2017
DreamSketch: Early Stage 3D Design Explorations with Sketching and Generative DesignWe present DreamSketch, a novel 3D design interface that combines the…
2014
Special Issue: Simulation for Architecture and Urban DesignThis special issue celebrates five annual SimAUD (Simulation for…
2014
Active Printed Materials for Complex Self-Evolving DeformationsWe propose a new design of complex self-evolving structures that vary…
2008
Hardware implementation of a bio-plausible neuron model for evolution and growth of spiking neural networks on FPGAThe natural-language approach to identifying biological analogies…
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