Script-based Multi-video Summarization
Date Issued
2005
Date
2005
Author(s)
Cheng, Yu-Jen
DOI
en-US
Abstract
Automatic video summarization methods have attracted research attentions for a long time. Previous works can be classified into two categories: keyframe-based video summarization and dynamic video summarization. Recently the rapid growth of computing power and storage capacity make it possible to generate dynamic video summaries much faster. However there is no previous work on generating video summaries according to specific user information needs and experiments on a multi-video environment. In this thesis we will explore the problem of script-based video summarization, in which the information needs are contained in a user script.
We first use linguistic information and shot boundary detection results to divide videos into segments, which are the foundation stones of building the summary. Then information retrieval system retrieves relevant segments using the user script as queries, and captions of the segments as documents. After sub-shot clustering, visual importance scores are evaluated for each segment based on the clustering results of its constituent sub-shots. The relevant score and the visual importance score are combined to select both informative and vivid segments.
To achieve better coherence, segment re-ordering is applied. We analyze the audio and video content, finding the editing rhythm and editing heuristics, and then develop an algorithm for visual coherence. Experiments show that this algorithm has better coherence compared with other text-based algorithm, without loss of informativeness.
Subjects
影像摘要
Video
Summarization
Type
thesis