Efficient Non-chronological Dynamic Video Abstraction Using the Rack-Through Method

2011 ◽  
pp. 472-474
Author(s):  
E. Jayabalan ◽  
A. Krishnan
Keyword(s):  
Video Abstraction

Automatic home video abstraction using audio contents

2002 ◽  
Author(s):  
Ming Zhao ◽  
Chun Chen ◽  
Caifu Chen ◽  
JiaJun Bu
Keyword(s):  
Home Video ◽  
Video Abstraction

Video abstraction based on the visual attention model and online clustering

2013 ◽  
Vol 28 (3) ◽  
pp. 241-253 ◽  
Author(s):  
Qing-Ge Ji ◽  
Zhi-Dang Fang ◽  
Zhen-Hua Xie ◽  
Zhe-Ming Lu
Keyword(s):  
Visual Attention ◽  
Online Clustering ◽  
Visual Attention Model ◽  
Attention Model ◽  
Video Abstraction

Real-time video abstraction

2006 ◽  
Vol 25 (3) ◽  
pp. 1221-1226 ◽  
Author(s):  
Holger Winnemöller ◽  
Sven C. Olsen ◽  
Bruce Gooch
Keyword(s):  
Real Time ◽  
Video Abstraction

Automatic personalized video abstraction for sports videos using metadata

2008 ◽  
Vol 41 (1) ◽  
pp. 1-25 ◽  
Author(s):  
Naoko Nitta ◽  
Yoshimasa Takahashi ◽  
Noboru Babaguchi
Keyword(s):  
Video Abstraction ◽  
Sports Videos ◽  
Personalized Video

Algorithm of Video Decomposition and Video Abstraction Generation Based on Face Detection and Recognition

2014 ◽  
Vol 644-650 ◽  
pp. 4620-4623
Author(s):  
Xiao Kang Wu ◽  
Cheng Gang Xie ◽  
Qin Lu
Keyword(s):  
Face Detection ◽  
Skin Color ◽  
Feature Matching ◽  
Light Conditions ◽  
Key Frame ◽  
Video Abstraction ◽  
National University ◽  
Spectrum Feature ◽  
Face Detection And Recognition ◽  
Detection And Recognition

ion generation based on face detection and recognitionXiaokang Wu1, a, Chenggang Xie2, b, Qin Lu2, c1 National University Of Defense Technology, Changsha 410073, China;[email protected], [email protected],Keywords: face detection, face recognition, key frame, video abstractionAbstract. In order to facilitate users browse the behaviors and expressions of interesting objects in a video quickly, need to remove the redundancy information and extract key frames related to the object interested. This paper uses a fast face detection based on skin color, and recognition technology using spectrum feature matching, decompose the coupling video, and classify frames related to the object into different sets, generate a different video abstraction of each object. Experimental results show that the algorithm under different light conditions has better practicability.

Video abstraction

2007 ◽  
Vol 3 (1) ◽  
pp. 3 ◽  
Author(s):  
Ba Tu Truong ◽  
Svetha Venkatesh
Keyword(s):  
Video Abstraction
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