Premium
Comprehensible Video Thumbnails
Author(s) -
Kim Jongdae,
Gray Charles,
Asente Paul,
Collomosse John
Publication year - 2015
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/cgf.12550
Subject(s) - thumbnail , computer science , computer vision , artificial intelligence , salient , retargeting , motion (physics) , motion compensation , coherence (philosophical gambling strategy) , visualization , computer graphics (images) , image (mathematics) , mathematics , statistics
We present the Comprehensible Video Thumbnail; an automatically generated visual précis 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.