Publication: IMOTION — a content-based video retrieval engine
Program
KU-Authors
KU Authors
Co-Authors
Rossetto, Luca
Giangreco, Ivan
Schuldt, Heiko
Dupont, Stèphane
Seddati, Omar
Publication Date
Language
Embargo Status
Journal Title
Journal ISSN
Volume Title
Alternative Title
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.
Source
Publisher
Springer
Subject
Computer science
Citation
Has Part
Source
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Book Series Title
Edition
DOI
10.1007/978-3-319-14442-9_24