Paper Info
Title
Automated production of TV program trailer using electronic program guide
Abstract
This paper proposes two automated methods for producing TV program trailers (short video clips to advertise the program). Program trailers are useful as the representative video of a content retrieval system that operates in a large archive of program videos. The two methods employ introductory descriptions from electronic program guides. The first method is based on the sentence similarity between the closed caption and the introductory text of the target program. We extract closed caption sentences that have the highest similarity for each introductory sentence, and then connect the corresponding video segments to make the representative video. A Bayesian belief network is used to calculate the similarity. The second method extracts several sentences that have the same textual features as those of a general introductory text, and determines the corresponding video sections. The features are learned by using the AdaBoost algorithm. These methods were used to generate trailers for actual TV programs, by which their effectiveness was verified.
Year
DOI
Venue
2007
10.1145/1282280.1282287
CIVR
Keywords
Field
DocType
automated production,short video clip,program video,general introductory text,corresponding video segment,actual tv program,tv program trailer,corresponding video section,target program,electronic program guide,representative video,adaboost,closed caption,bayesian belief network
Electronic program guide,Computer vision,Closed captioning,Content retrieval,AdaBoost,Information retrieval,Computer science,Sentence similarity,Bayesian network,Artificial intelligence,Sentence,Trailer
Conference
Citations 
PageRank 
References 
7
0.57
17
Authors
3
Name
Order
Citations
PageRank
Yoshihiko Kawai117913.37
Hideki Sumiyoshi2439.08
Nobuyuki Yagi36514.03