Abstract
Summarizing long unconstrained videos is gaining importance in surveillance, web-based video browsing, and video-archival applications. Summarizing a video requires one to identify key aspects that contain the essence of the video. In this paper, we propose an approach that optimizes two criteria that a video summary should embody. The first criterion, coverage, requires that the summary be able to represent the original video well. The second criterion, diversity, requires that the elements of the summary be as distinct from each other as possible. Given a user-specified summary length, we propose a cost function to measure the quality of a summary. The problem of generating a prcis is then reduced to a combinatorial optimization problem of minimizing the proposed cost function. We propose an efficient method to solve the optimization problem. We demonstrate through experiments (on KTH data, unconstrained skating video, a surveillance video, and a YouTube home video) that optimizing the proposed criterion results in meaningful video summaries over a wide range of scenarios. Summaries thus generated are then evaluated using both quantitative measures and user studies.
Original language | English (US) |
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Article number | 5510158 |
Pages (from-to) | 853-868 |
Number of pages | 16 |
Journal | IEEE Transactions on Multimedia |
Volume | 12 |
Issue number | 8 |
DOIs | |
State | Published - Dec 2010 |
Keywords
- Exemplar selection
- K-means
- Ncut
- shot segmentation
- video summarization
ASJC Scopus subject areas
- Signal Processing
- Media Technology
- Computer Science Applications
- Electrical and Electronic Engineering