Login (DCU Staff Only)
Login (DCU Staff Only)

DORAS | DCU Research Repository

Explore open access research and scholarly works from DCU

Advanced Search

IMOTION — A Content-Based Video Retrieval Engine

Rossetto, Luca orcid logoORCID: 0000-0002-5389-9465, Giangreco, Ivan, Schuldt, Heiko, Dupont, Stéphane, Seddati, Omar, Sezgin, Metin and Sahillioğlu, Yusuf (2015) IMOTION — A Content-Based Video Retrieval Engine. In: MultiMedia Modeling. MMM 2015, 5-7 Jan. 2015, Sydney, NSW, Australia. ISBN 978-3-319-14442-9

Abstract
This paper introduces the IMOTION system, a sketch-based video retrieval engine supporting multiple query paradigms. For vector space retrieval, the IMOTION system exploits a large variety of lowlevel image and video features, as well as high-level spatial and temporal features that can all be jointly used in any combination. In addition, it supports dedicated motion features to allow for the specification of motion within a video sequence. For query specification, the IMOTION system supports query-by-sketch interactions (users provide sketches of video frames), motion queries (users specify motion across frames via partial flow fields), query-by-example (based on images) and any combination of these, and provides support for relevance feedback.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Information retrieval
Computer Science > Multimedia systems
Computer Science > Information storage and retrieval systems
DCU Faculties and Centres:UNSPECIFIED
Published in: MultiMedia Modeling. MMM 2015. Lecture Notes in Computer Science. Lecture Notes in Computer Science 8936. Springer Nature. ISBN 978-3-319-14442-9
Publisher:Springer Nature
Official URL:https://link.springer.com/chapter/10.1007/978-3-31...
Copyright Information:Authors
ID Code:32429
Deposited On:13 Mar 2026 12:28 by Luca Rossetto . Last Modified 13 Mar 2026 12:28
Documents

Full text available as:

[thumbnail of VBS15_imotion.pdf]
Preview
PDF - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Creative Commons: Attribution 4.0
546kB
Downloads

Downloads

Downloads per month over past year

Archive Staff Only: edit this record