Fusing semantics, observability, reliability and diversity of concept detectors for video search

Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and...

Full description

Saved in:
Bibliographic Details
Main Authors: WEI, Xiao-Yong, NGO, Chong-wah
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2008
Subjects:
Online Access:https://ink.library.smu.edu.sg/sis_research/6368
https://ink.library.smu.edu.sg/context/sis_research/article/7371/viewcontent/p81_wei.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English
id sg-smu-ink.sis_research-7371
record_format dspace
spelling sg-smu-ink.sis_research-73712021-11-23T02:49:23Z Fusing semantics, observability, reliability and diversity of concept detectors for video search WEI, Xiao-Yong NGO, Chong-wah Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred from semantic reasoning such as using ontology. To facilitate the selection of detectors, we propose the building of two vector spaces: semantic space (SS) and observability space (OS). We categorize the set of detectors selected separately from SS and OS into four types: anchor, bridge, positive and negative concepts. A multi-level fusion strategy is proposed to novelly combine detectors, allowing the enhancement of detector reliability while enabling the observability, semantics and diversity of concepts being utilized for query answering. By experimenting the proposed approach on TRECVID 2005-2007 datasets and queries, we demonstrate the significance of considering observability, reliability and diversity, in addition to the semantics of detectors to queries. 2008-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6368 info:doi/10.1145/1459359.1459371 https://ink.library.smu.edu.sg/context/sis_research/article/7371/viewcontent/p81_wei.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Concept-based video search Detector selection and fusion Data Storage Systems Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Concept-based video search
Detector selection and fusion
Data Storage Systems
Theory and Algorithms
spellingShingle Concept-based video search
Detector selection and fusion
Data Storage Systems
Theory and Algorithms
WEI, Xiao-Yong
NGO, Chong-wah
Fusing semantics, observability, reliability and diversity of concept detectors for video search
description Effective utilization of semantic concept detectors for large-scale video search has recently become a topic of intensive studies. One of main challenges is the selection and fusion of appropriate detectors, which considers not only semantics but also the reliability of detectors, observability and diversity of detectors in target video domains. In this paper, we present a novel fusion technique which considers different aspects of detectors for query answering. In addition to utilizing detectors for bridging the semantic gap of user queries and multimedia data, we also address the issue of "observability gap" among detectors which could not be directly inferred from semantic reasoning such as using ontology. To facilitate the selection of detectors, we propose the building of two vector spaces: semantic space (SS) and observability space (OS). We categorize the set of detectors selected separately from SS and OS into four types: anchor, bridge, positive and negative concepts. A multi-level fusion strategy is proposed to novelly combine detectors, allowing the enhancement of detector reliability while enabling the observability, semantics and diversity of concepts being utilized for query answering. By experimenting the proposed approach on TRECVID 2005-2007 datasets and queries, we demonstrate the significance of considering observability, reliability and diversity, in addition to the semantics of detectors to queries.
format text
author WEI, Xiao-Yong
NGO, Chong-wah
author_facet WEI, Xiao-Yong
NGO, Chong-wah
author_sort WEI, Xiao-Yong
title Fusing semantics, observability, reliability and diversity of concept detectors for video search
title_short Fusing semantics, observability, reliability and diversity of concept detectors for video search
title_full Fusing semantics, observability, reliability and diversity of concept detectors for video search
title_fullStr Fusing semantics, observability, reliability and diversity of concept detectors for video search
title_full_unstemmed Fusing semantics, observability, reliability and diversity of concept detectors for video search
title_sort fusing semantics, observability, reliability and diversity of concept detectors for video search
publisher Institutional Knowledge at Singapore Management University
publishDate 2008
url https://ink.library.smu.edu.sg/sis_research/6368
https://ink.library.smu.edu.sg/context/sis_research/article/7371/viewcontent/p81_wei.pdf
_version_ 1770575943309459456