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Updated: Oct 22, 2025
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News Video Summarization Combining SURF and Color Histogram Features
Buyun Liang1, Na Li2, Zheng He1
1School of Computer Science, Wuhan University, Wuhan 430072, China.
Entropy (Basel, Switzerland)
|August 27, 2021
Summary
This study introduces an improved news video summarization method using SURF features and clustering to create concise video sketches. The approach accurately and quickly identifies key frames, overcoming limitations of existing techniques.
Area of Science:
- Computer Science
- Information Technology
- Digital Media
Background:
- Exponential growth in news video data necessitates efficient browsing methods.
- Existing video summarization algorithms struggle with varying shot complexity.
Purpose of the Study:
- To propose an advanced news video summarization technique.
- To address limitations in current algorithms regarding shot complexity.
- To generate accurate and rapid video sketches.
Main Methods:
- Extraction and matching of SURF features between adjacent frames.
- Detection of shot boundaries (abrupt and gradual) using similarity scores and double thresholds.
- Clustering of video frame color histograms with an improved algorithm, merging small clusters.
- Selection of key frames closest to cluster centers.
Main Results:
- The proposed method demonstrates superior accuracy and speed compared to alternatives.
- Experimental validation on public and self-built datasets confirms effectiveness.
- Generated key frames exhibit low redundancy.
Conclusions:
- The developed method effectively summarizes news videos by selecting representative key frames.
- It offers a reliable and efficient solution for browsing large news video archives.
- The technique successfully handles variations in shot complexity for better summarization.
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