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iAutoMotion – an Autonomous Content-Based Video Retrieval Engine

Rossetto, Luca orcid logoORCID: 0000-0002-5389-9465, Giangreco, Ivan, Tanase, Claudiu, Schuldt, Heiko, Dupont, Stéphane, Seddati, Omar, Sezgin, Metin and Sahillioğlu, Yusuf (2016) iAutoMotion – an Autonomous Content-Based Video Retrieval Engine. In: 22nd International Conference on MultiMedia Modeling, 4-6 Jan. 2016, Miami, USA. ISBN 978-3-319-27670-0

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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Image processing
Computer Science > Information retrieval
Computer Science > Multimedia systems
Computer Science > Information storage and retrieval systems
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: MMM 2016: Proceedings, Part I, of the 22nd International Conference on MultiMedia Modeling. 9516. Springer Nature. ISBN 978-3-319-27670-0
Publisher:Springer Nature
Official URL:https://dl.acm.org/doi/proceedings/10.5555/2993066
Copyright Information:Authors
ID Code:32424
Deposited On:20 Mar 2026 09:59 by Luca Rossetto . Last Modified 20 Mar 2026 09:59
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