Paper Info
Title
Video search and indexing with reinforcement agent for interactive multimedia services
Abstract
In this study, we present a video search and indexing system based on the state support vector (SVM) network, video graph, and reinforcement agent for recognizing and organizing video events. In order to enhance the recognition performance of the state SVM network, two innovative techniques are presented: state transition correction and transition quality estimation. The classification results are also merged into the video indexing graph, which facilitates the search speed. A reinforcement algorithm with an efficient scheduling scheme significantly reduces both the power consumption and time. The experimental results show the proposed state SVM network was able to achieve a precision rate as high as 83.83% and the query results of the indexing graph reached 80% accuracy. The experiments also demonstrate the performance and feasibility of our system.
Year
DOI
Venue
2013
10.1145/2423636.2423643
ACM Trans. Embedded Comput. Syst.
Keywords
Field
DocType
indexing system,indexing graph,video graph,proposed state svm network,video indexing graph,state support vector,reinforcement agent,state svm network,interactive multimedia service,video search,video event,state transition correction,performance,algorithms,design
Data mining,Graph,Scheduling (computing),Computer science,Support vector machine,Search engine indexing,Interactive media,Reinforcement,Multimedia information systems,Power consumption
Journal
Volume
Issue
ISSN
12
2
1539-9087
Citations 
PageRank 
References 
15
0.65
21
Authors
4
Name
Order
Citations
PageRank
Anand Paul1292.70
Bo-Wei Chen226230.12
Karunanithi Bharanitharan3383.51
Jhing-fa Wang4982114.31