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
Advisor
Publication Date
Language
English
Journal Title
Journal ISSN
Volume 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.
Description
Source:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher:
Springer
Keywords:
Subject
Computer science