Video Shot Detection based on SIFT Features and Video Summarization using Expectation-Maximization

被引：0

作者：

Majumdar, Jharna ^{[1
,2
]}

Awale, Manish ^{[2
]}

Kumar, Santhosh K. L. ^{[2
]}

机构：

[1] Nitte Meenakshi Inst Technol, R&D, Bengaluru, India

[2] Nitte Meenakshi Inst Technol, Dept M Tech CSE, Bengaluru, India

来源：

2018 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI) | 2018年

关键词：

SIFT; Expectation Maximization; Video Shot Detection; Video Summary; and Quality Metrics;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Video Shot Detection is utilized to detect change of scene in the video. Video Summarization gives most useful frames to create the conceptual information of the given video. In this paper, we have coordinated both the ideas of shot detection and summarization for the better result of the outcomes. The SIFT features are extracted from the frames and compared with consecutive frames for Video Shot detection and the Video Summarization is done using Expected- Maximization. The shot frames of Video shot detection are utilized as contribution for the Video Summarization. The quality metric parameters are utilized to assess the strength of the key frame extraction.

引用

页码：1033 / 1037

页数：5

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