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Empowering Semantic Indexing with Focus of Attention

Authors:
Kimiaki Shirahama
Tadashi Matsumura
Marcin Grzegorzek
Kuniaki Uehara

Keywords: Semantic indexing, Focus of attention, Weakly supervised learning, Usefulness of salient regions

Abstract:
This paper addresses Semantic INdexing (SIN) to detect concepts like Person and Car in video shots. One main obstacle is the abundant information contained in a shot where multiple concepts are displayed at the same time. In other words, the detection of a target concept is adversely affected by other concepts which are incidentally shown in the same shot. We assume that a user can recognise the target concept when it appears in a salient region which attracts his/her attention. Based on this, we introduce a SIN method which utilises Focus of Attention (FoA) to extract a salient region in a shot, and constructs a feature emphasising that salient region. In addition, we develop a Weakly Supervised Learning (WSL) method to efficiently create training shots for FoA, and a shot filtering method to examine the usefulness of salient regions. Experimental results show the effectiveness of our SIN method using FoA.

Pages: 33 to 36

Copyright: Copyright (c) IARIA, 2015

Publication date: April 19, 2015

Published in: conference

ISSN: 2308-4448

ISBN: 978-1-61208-400-8

Location: Barcelona, Spain

Dates: from April 19, 2015 to April 24, 2015