Method for endobronchial video parsing

2016 ◽  
Author(s):  
Patrick D. Byrnes ◽  
William E. Higgins
Keyword(s):  
Video Parsing

scholarly journals Surveillance Video Parsing with Single Frame Supervision

2017 ◽  
Author(s):  
Si Liu ◽  
Changhu Wang ◽  
Ruihe Qian ◽  
Han Yu ◽  
Renda Bao ◽  
...  
Keyword(s):  
Surveillance Video ◽  
Single Frame ◽  
Video Parsing

Audiovisual integration with Segment Models for tennis video parsing

2008 ◽  
Vol 111 (2) ◽  
pp. 142-154 ◽  
Author(s):  
Manolis Delakis ◽  
Guillaume Gravier ◽  
Patrick Gros
Keyword(s):  
Audiovisual Integration ◽  
Video Parsing

TVParser: An automatic TV video parsing method

CVPR 2011 ◽  
2011 ◽  
Author(s):  
Chao Liang ◽  
Changsheng Xu ◽  
Jian Cheng ◽  
Hanqing Lu
Keyword(s):  
Video Parsing

Video Summarization by Redundancy Removing and Content Ranking

2011 ◽  
pp. 91-101
Author(s):  
Tao Wang ◽  
Yue Gao ◽  
Patricia Wang ◽  
Wei Hu ◽  
Jianguo Li ◽  
...  
Keyword(s):  
Video Summarization ◽  
Time Constraint ◽  
Key Frame ◽  
Video Summary ◽  
Video Parsing ◽  
Content Ranking

Video summary is very important for users to grasp a whole video’s content quickly for efficient browsing and editing. In this chapter, we propose a novel video summarization approach based on redundancy removing and content ranking. Firstly, by video parsing and cast indexing, the approach constructs a story board to let user know about the main scenes and the main actors in the video. Then it removes redundant frames to generate a “story-constraint summary” by key frame clustering and repetitive segment detection. To shorten the video summary length to a target length, “time-constraint summary” is constructed by important factor based content ranking. Extensive experiments are carried out on TV series, movies, and cartoons. Good results demonstrate the effectiveness of the proposed method.

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