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iAutoMotion - an Autonomous Content-based Video Retrieval Engine
ConferencePaper (Artikel, die in Tagungsbänden erschienen sind)
 
ID 3342709
Author(s) Rossetto, Luca; Giangreco, Ivan; Tănase, Claudiu; Schuldt, Heiko; Dupont, Stéphane; Seddati, Omar; Sezgin, Metin; Sahillioğlu, Yusuf
Author(s) at UniBasel Schuldt, Heiko
Rossetto, Luca
Giangreco, Ivan
Tanase, Claudiu-Ioan
Year 2016
Title iAutoMotion - an Autonomous Content-based Video Retrieval Engine
Editor(s) Tian, Qi; Sebe, Nicu, Nicu; Qi, Guo-Jun; Huet, Benoit; Hong, Richang; Liu, Xueliang
Book title (Conference Proceedings) Proceedings of the 22nd International Conference on MultiMedia Modeling (MMM 2016)
Volume 2
Place of Conference Miami, FL, USA
Year of Conference 2016
Publisher Springer
Place of Publication Cham
Pages 383-387
ISSN/ISBN 0302-9743 ; 1611-3349 ; 978-3-319-27670-0 ; 978-3-319-27671-7
Abstract This paper introduces iAutoMotion, an autonomous video retrieval system that requires only minimal user input. It is based on the video retrieval engine IMOTION. iAutoMotion uses a camera to capture the input for both visual and textual queries and performs query composition, retrieval, and result submission autonomously. For the visual tasks, it uses various visual features applied to the captured query images; for the textual tasks, it applies OCR and some basic natural language processing, combined with object recognition. As the iAutoMotion system does not conform to the VBS 2016 rules, it will participate as unofficial competitor and serve as a benchmark for the manually operated systems.
Series title Lecture Notes in Computer Science book series (LNCS)
Number 9517
edoc-URL http://edoc.unibas.ch/40149/
Full Text on edoc No
Digital Object Identifier DOI 10.1007/978-3-319-27674-8
 
   

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