DocumentCode :
588180
Title :
Large Scale Video Analytics: On-demand, iterative inquiry for moving image research
Author :
Kuhn, Volker ; Craig, Ashley ; Franklin, K. ; Simeone, M. ; Arora, Rajkumar ; Bock, D. ; Marini, Luigi
Author_Institution :
USC, Los Angeles, CA, USA
fYear :
2012
fDate :
8-12 Oct. 2012
Firstpage :
1
Lastpage :
5
Abstract :
Video is exploding as a means of communication and expression, and the resultant archives are massive, disconnected datasets. Thus, scholars´ ability to research this crucial aspect of contemporary culture is severely hamstrung by limitations in semantic image retrieval, incomplete metadata, and the lack of a precise understanding of the actual content of any given archive. Our aim in the Large Scale Video Analytics (LSVA) project is to address obstacles in both image-retrieval and research that uses extreme-scale archives of video data that employs a human-machine hybrid process for analyzing moving images. We propose an approach that 1) places more interpretive power in the hands of the human user through novel visualizations of video data, and 2) uses a customized on-demand configuration that enables iterative queries.
Keywords :
image retrieval; iterative methods; video signal processing; LSVA; disconnected datasets; image research; image retrieval; incomplete metadata; interpretive power; iterative inquiry; iterative queries; large scale video analytics; semantic image retrieval; video data; video data visualizations; Biomedical imaging; Data visualization; Films; Image retrieval; Motion pictures; Streaming media; High Performance Computing; Image Edge Detection; Image Retrieval; Multimedia Databases; Software; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Science (e-Science), 2012 IEEE 8th International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
978-1-4673-4467-8
Type :
conf
DOI :
10.1109/eScience.2012.6404446
Filename :
6404446
Link To Document :
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