Human Augmented Cognition Based on Integration of Visual and Auditory Information
Identifieur interne : 003934 ( Main/Merge ); précédent : 003933; suivant : 003935Human Augmented Cognition Based on Integration of Visual and Auditory Information
Auteurs : Jae Won [Corée du Sud] ; Wono Lee [Corée du Sud] ; Sang-Woo Ban [Corée du Sud] ; Minook Kim [Corée du Sud] ; Hyung-Min Park [Corée du Sud] ; Minho Lee [Corée du Sud]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2010.
Abstract
Abstract: In this paper, we propose a new multiple sensory fused human identification model for providing human augmented cognition. In the proposed model, both facial features and mel-frequency cepstral coefficients (MFCCs) are considered as visual features and auditory features for identifying a human, respectively. As well, an adaboosting model identifies a human using the integrated sensory features of both visual and auditory features. In the proposed model, facial form features are obtained from the principal component analysis (PCA) of a human’s face area localized by an Adaboost algorithm in conjunction with a skin color preferable attention model. Moreover, MFCCs are extracted from human speech. Thus, the proposed multiple sensory integration model is aimed to enhance the performance of human identification by considering both visual and auditory complementarily working under partly distorted sensory environments. A human augmented cognition system with the proposed human identification model is implemented as a goggle type, on which it presents information such as unknown people’s profile based on human identification. Experimental results show that the proposed model can plausibly conduct human identification in an indoor meeting situation.
Url:
DOI: 10.1007/978-3-642-15246-7_50
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Sud</country><wicri:regionArea>Department of Electronic Engineering, Sogang University, 1 Shinsu-Dong, Mapo-Gu, 121-742, Seoul</wicri:regionArea><placeName><settlement type="city">Séoul</settlement></placeName></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Corée du Sud</country></affiliation></author><author><name sortKey="Lee, Minho" sort="Lee, Minho" uniqKey="Lee M" first="Minho" last="Lee">Minho Lee</name><affiliation wicri:level="1"><country xml:lang="fr">Corée du Sud</country><wicri:regionArea>School of Electrical Engineering and Computer Science, Kyungpook National University, 1370 Sankyuk-Dong, Puk-Gu, 702-701, Taegu</wicri:regionArea><wicri:noRegion>Taegu</wicri:noRegion></affiliation><affiliation wicri:level="1"><country wicri:rule="url">Corée du Sud</country></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2010</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">CCDFD3F3AE4C31DFC95EEE441D4754D601241AB9</idno><idno type="DOI">10.1007/978-3-642-15246-7_50</idno><idno type="ChapterID">50</idno><idno type="ChapterID">Chap50</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: In this paper, we propose a new multiple sensory fused human identification model for providing human augmented cognition. In the proposed model, both facial features and mel-frequency cepstral coefficients (MFCCs) are considered as visual features and auditory features for identifying a human, respectively. As well, an adaboosting model identifies a human using the integrated sensory features of both visual and auditory features. In the proposed model, facial form features are obtained from the principal component analysis (PCA) of a human’s face area localized by an Adaboost algorithm in conjunction with a skin color preferable attention model. Moreover, MFCCs are extracted from human speech. Thus, the proposed multiple sensory integration model is aimed to enhance the performance of human identification by considering both visual and auditory complementarily working under partly distorted sensory environments. A human augmented cognition system with the proposed human identification model is implemented as a goggle type, on which it presents information such as unknown people’s profile based on human identification. Experimental results show that the proposed model can plausibly conduct human identification in an indoor meeting situation.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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