Abstract

We present the Comprehensible Video Thumbnail; an automatically generated visual precis that summarizes salient objects and their dynamics within a video clip. Salient moving objects are detected within clips using a novel stochastic sampling technique that identifies, clusters and then tracks regions exhibiting affine motion coherence within the clip. Tracks are analyzed to determine salient instants at which motion and/or appearance changes significantly, and the Resulting objects arranged in a stylized composition optimized to reduce visual clutter and enhance understanding of scene content through classification and depiction of motion type and trajectory. The Result is an object-level visual gist of the clip, obtained with full automation and depicting content and motion with greater descriptive power that prior approaches. We demonstrate these benefits through a user study in which the comprehension of our video thumbnails is compared to the state of the art over a wide variety of sports footage.

Paper

Comprehensible Video Thumbnails
Jongdae Kim, Charles Gray , Paul Asente and John Collomosse
Proceedings of EUROGRAPHICS 2015

Data

The source of the datasets should be acknowledged in all publications in which it is used as by referencing the following paper and this web-site: Kim, J., Gray, C., Asente, P. and Collomosse, J. "Comprehensible Video Thumbnails", Computer Graphics Forum (Proceedings of Eurographics 2015) 34(2), 2015.
Download all videos

Dataset

Horse Riding
Horse Riding
Motor bike
Motor bike
Tiger running
Tiger running
Snow board
Snow board
Monkey bar
Car- failure case
Free run - failure case

Acknowledgments

This work has been supported in part by a funding gift from Adobe Systems and in part by an EPSRC Industrial CASE studentship from Sony R&D (BPRL)