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A Comparative Study for Known Item Visual Search Using Position Color Feature Signatures Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Enhanced Retrieval and Browsing in the IMOTION System

Authors : Luca Rossetto, Ivan Giangreco, Claudiu Tănase, Heiko Schuldt, Stéphane Dupont, Omar Seddati

Published in: MultiMedia Modeling

Publisher: Springer International Publishing

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Abstract

This paper presents the IMOTION system in its third version. While still focusing on sketch-based retrieval, we improved upon the semantic retrieval capabilities introduced in the previous version by adding more detectors and improving the interface for semantic query specification. In addition to previous year’s system, we increase the role of features obtained from Deep Neural Networks in three areas: semantic class labels for more entry-level concepts, hidden layer activation vectors for query-by-example and 2D semantic similarity results display. The new graph-based result navigation interface further enriches the system’s browsing capabilities. The updated database storage system \(\textsf {ADAM}_{{pro }}\) designed from the ground up for large scale multimedia applications ensures the scalability to steadily growing collections.

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previous chapter Concept-Based Interactive Search System
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Footnotes
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Metadata
Title
Enhanced Retrieval and Browsing in the IMOTION System
Authors
Luca Rossetto
Ivan Giangreco
Claudiu Tănase
Heiko Schuldt
Stéphane Dupont
Omar Seddati
Copyright Year
2017
Book
MultiMedia Modeling

Print ISBN: 978-3-319-51813-8

Electronic ISBN: 978-3-319-51814-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-51814-5_43