Comprehensible Video Thumbnails
Jongdae Kim, Charles Gray, Paul Asente, John Collomosse
In Computer Graphics Forum, 34(2), 2015.
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.
Keyword(s): Categories and Subject Descriptors (according to ACM CCS), E.3.8 [Imaging & Video]: Video Summarization—
Article URL: http://dx.doi.org/10.1111/cgf.12550
BibTeX format:
@article{CGF:CGF12550,
  author = {Jongdae Kim and Charles Gray and Paul Asente and John Collomosse},
  title = {Comprehensible Video Thumbnails},
  journal = {Computer Graphics Forum},
  volume = {34},
  number = {2},
  pages = {167--177},
  year = {2015},
}
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