Paper Info
Title
Suggestion-Based Interactive Video Digest Design By User-System Cooperative Evolution
Abstract
This paper proposes a suggestion-based interactive evolution method for video summarization, which attempts to enhance users' creative thought process without disturbing user edit operation. Although solutions of video summarization are time-varying, a few solutions can be evaluated in parallel. Therefore, the proposed method optimizes summarized video in background asynchronously with user operation. The background optimization is modeled as bi-objective optimization of user preference estimated by user operations and solution novelty. In this, Pareto solutions are stored to an archive and solutions are selected to suggest to the user based on alpha-domination. Experimental results using an eye-tracking device have revealed that the proposed method enhances convergent thinking rather than divergent thinking.
Year
Venue
Keywords
2015
2015 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
interactive evolutionary computation, cooperative evolution by user and system, multiobjective optimization, novelty search, video summarization
Field
DocType
Citations 
Interactive video,Automatic summarization,Divergent thinking,Mathematical optimization,Convergent thinking,Computer science,Graphical user interface,Artificial intelligence,User interface design,User interface,Pareto principle,Machine learning
Conference
0
PageRank 
References 
Authors
0.34
9
2
Name
Order
Citations
PageRank
Nakamura, H.141.54
Satoshi Ono221939.83