Skims are highly condensed
clips (say 10 seconds) of long video sequences. They are very useful for
content browsing and on-demand summaries. Conventional methods for skim
generation primarily relied on text matching or object detection, but
did not consider the production syntax and human perception of audio-visual
In this project, we study (1)
how content condensation affects perceptual quality (2) how production
syntax can be preserved and (3) how audio and visual media should be condensed
One key contribution of ours
is the formulation of a rigorous utility-based framework for optimal skim
determination, rather than relying on heuristic rules. Subjective experiments
show performance improvement by the new method.
H. Sundaram, L. Xie, S.-F. Chang, A
Utility Framework for the Automatic Generation of Audio-Visual Skims,
ACM Multimedia, Juan Les Pins, France, December 2002 .
(Best Student Paper Award)
H. Sundaram, Segmentation,
Structure Detection and Summarization of Multimedia Sequences, Doctoral
Dissertation, Graduate School of Arts and Sciences, Columbia University,
2002 (Advisor: Prof. Chang).
H. Sundaram, S.-F. Chang, Constrained
Utility Maximization for generating Visual Skims, iEEE Workshop on
Content-based Access of Image and Video Libraries (CBAIVL'2001) Dec. 2001
Kauai, HI USA.
H. Sundaram and S.-F Chang, Condensing
Computable Scenes using Visual Complexity and Film Syntax Analysis,
IEEE Conference on Multimedia and Exhibition, Tokyo, Japan, Aug. 22-25,
problems or questions regarding this web site contact The
June 12, 2002.