A dynamic key frame extraction based on a multi-feature descriptor

Zhang Meng; Zhang Honggang; Chai Lunshao; Li Qiaohong

Chinese︱Feedback︱Save this page

• Elaborating Academic Views 　　　　 • Exchanging Innovative Ideas
• Protecting Intellectual Properties 　　• Fast Sharing Science Papers

Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China

Home > Papers

A dynamic key frame extraction based on a multi-feature descriptor

Zhang Meng,Zhang Honggang *,Chai Lunshao,Li Qiaohong

Pattern Recognition and Intelligent System Lab, Beijing University of Posts and Telecommunications, Beijing 100876

*Correspondence author

#Submitted by

Subject:

Funding: Fundamental Research Funds for the Central Universities under Grant（No.No.2009RC0130）, National Natural Science Foundation of China under Grant（No.No.61005004）

Opened online: 6 January 2012

Accepted by: none

Citation: Zhang Meng,Zhang Honggang,Chai Lunshao.A dynamic key frame extraction based on a multi-feature descriptor[OL]. [ 6 January 2012] http://en.paper.edu.cn/en_releasepaper/content/4458273

Key frame extraction is one of the basic procedures in video retrieval. Key frame extraction aims at finding a small collection of image frame sequences extracted from a video sequence in order to reduce the amount of data that must be examined. Efficient key frame extraction techniques will facilitate the video browsing systems, which have wide applications in real world. In this paper, we proposed an innovative approach to the selection of key frames of a video sequence. First, two descriptors of color and edge features are used to describe visual content, and are integrated as a muti-feature descriptor, then we analyze the differences between two consecutive frames of a video sequence. Finally, key frames are extracted by the dynamic threshold algorithm. Experimental results show that the proposed algorithm can dynamically and rapidly select a variable number of key frames within each sequence and can achieve high compression ratio and high fidelity.

Keywords:video retrieval; color and edge features; dynamic threshold algorithm

For this paper

● PDF (0B)
● Revision 0 　　
● Print this paper
● Recommend this paper to a friend
● Add to my favorite list

Saved Papers

Please enter a name for this paper to be shown in your personalized Saved Papers list

Tags

Add yours

Related Papers

Other similar papers
● Automatic Video Summariz...

Statistics

PDF Downloaded	263
Bookmarked	0
Recommend	5
Comments	Array

Submit your papers

Alert Name:
Alerting to:
Authentication email will be sent to your email address in 24 hours
Frequency:
Email Message Format:	Plain text Graphical(HTML)

Complete the form below and we will recommend the selected titles to your friends on your behalf. * Indicates a required field.
Your name*:
Your email address*:
Recipient's name*:
Recipient's email address*:
(multiple recipient's names and email addresses should be separated with semicolons)
Your comments:	I thought you would find the page(s) useful.

Your name:
Your email address:
Recipient's name:
Recipient's email address:
(multiple recipient's names and email addresses should be separated with semicolons)
Your comments:	I thought you would find this page useful.

Disclaimer: This message was sent to your friend using the "Send it to a friend" facility on the Sciencepaper Online’ WWW site, http://www.paper.edu.cn/en. The Sciencepaper Online is not responsible for the content of this email, and anything said in this email does not necessarily reflect the Sciencepaper Online's views.

	Check out RSS, or use RSS reader to subscribe this item

Saved Papers