EEG analysis for implicit tagging of video data

Sander Koelstra; Christian Mühl; Ioannis Patras

doi:10.1109/ACII.2009.5349482

EEG analysis for implicit tagging of video data

Sander Koelstra, Christian Mühl, Ioannis Patras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

43 Citations (Scopus)

90 Downloads (Pure)

Abstract

In this work, we aim to find neuro-physiological indicators to validate tags attached to video content. Subjects are shown a video and a tag and we aim to determine whether the shown tag was congruent with the presented video by detecting the occurrence of an N400 event-related potential. Tag validation could be used in conjunction with a vision-based recognition system as a feedback mechanism to improve the classification accuracy for multimedia indexing and retrieval. An advantage of using the EEG modality for tag validation is that it is a way of performing implicit tagging. This means it can be performed while the user is passively watching the video. Independent Component Analysis and repeated measures ANOVA are used for analysis. Our experimental results show a clear occurrence of the N400 and a significant difference in N400 activation between matching and non-matching tags.

Original language	English
Title of host publication	Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009
Place of Publication	Los Alamitos, NJ
Publisher	IEEE
Pages	27-32
Number of pages	6
Volume	2
ISBN (Print)	978-1-4244-4799-2
DOIs	https://doi.org/10.1109/ACII.2009.5349482
Publication status	Published - 2009
Event	3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009 - De Rode Hoed, Amsterdam, Netherlands Duration: 10 Sept 2009 → 12 Sept 2009 Conference number: 3

Conference

Conference	3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009
Abbreviated title	ACII
Country/Territory	Netherlands
City	Amsterdam
Period	10/09/09 → 12/09/09

Keywords

METIS-264313
IR-69486
Multimedia tagging
EEG
HMI-MI: MULTIMODAL INTERACTIONS
Multimedia Retrieval
EWI-17167
Category retrieval
HMI-MR: MULTIMEDIA RETRIEVAL
N400

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10.1109/ACII.2009.5349482

Cite this

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title = "EEG analysis for implicit tagging of video data",

abstract = "In this work, we aim to find neuro-physiological indicators to validate tags attached to video content. Subjects are shown a video and a tag and we aim to determine whether the shown tag was congruent with the presented video by detecting the occurrence of an N400 event-related potential. Tag validation could be used in conjunction with a vision-based recognition system as a feedback mechanism to improve the classification accuracy for multimedia indexing and retrieval. An advantage of using the EEG modality for tag validation is that it is a way of performing implicit tagging. This means it can be performed while the user is passively watching the video. Independent Component Analysis and repeated measures ANOVA are used for analysis. Our experimental results show a clear occurrence of the N400 and a significant difference in N400 activation between matching and non-matching tags.",

keywords = "METIS-264313, IR-69486, Multimedia tagging, EEG, HMI-MI: MULTIMODAL INTERACTIONS, Multimedia Retrieval, EWI-17167, Category retrieval, HMI-MR: MULTIMEDIA RETRIEVAL, N400",

author = "Sander Koelstra and Christian M{\"u}hl and Ioannis Patras",

year = "2009",

doi = "10.1109/ACII.2009.5349482",

language = "English",

isbn = "978-1-4244-4799-2",

volume = "2",

pages = "27--32",

booktitle = "Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009",

publisher = "IEEE",

address = "United States",

note = "3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009, ACII ; Conference date: 10-09-2009 Through 12-09-2009",

}

Koelstra, S, Mühl, C & Patras, I 2009, EEG analysis for implicit tagging of video data. in Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. vol. 2, IEEE, Los Alamitos, NJ, pp. 27-32, 3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009, Amsterdam, Netherlands, 10/09/09. https://doi.org/10.1109/ACII.2009.5349482

EEG analysis for implicit tagging of video data. / Koelstra, Sander; Mühl, Christian; Patras, Ioannis.
Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009. Vol. 2 Los Alamitos, NJ: IEEE, 2009. p. 27-32.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - EEG analysis for implicit tagging of video data

AU - Koelstra, Sander

AU - Mühl, Christian

AU - Patras, Ioannis

N1 - Conference code: 3

PY - 2009

Y1 - 2009

N2 - In this work, we aim to find neuro-physiological indicators to validate tags attached to video content. Subjects are shown a video and a tag and we aim to determine whether the shown tag was congruent with the presented video by detecting the occurrence of an N400 event-related potential. Tag validation could be used in conjunction with a vision-based recognition system as a feedback mechanism to improve the classification accuracy for multimedia indexing and retrieval. An advantage of using the EEG modality for tag validation is that it is a way of performing implicit tagging. This means it can be performed while the user is passively watching the video. Independent Component Analysis and repeated measures ANOVA are used for analysis. Our experimental results show a clear occurrence of the N400 and a significant difference in N400 activation between matching and non-matching tags.

AB - In this work, we aim to find neuro-physiological indicators to validate tags attached to video content. Subjects are shown a video and a tag and we aim to determine whether the shown tag was congruent with the presented video by detecting the occurrence of an N400 event-related potential. Tag validation could be used in conjunction with a vision-based recognition system as a feedback mechanism to improve the classification accuracy for multimedia indexing and retrieval. An advantage of using the EEG modality for tag validation is that it is a way of performing implicit tagging. This means it can be performed while the user is passively watching the video. Independent Component Analysis and repeated measures ANOVA are used for analysis. Our experimental results show a clear occurrence of the N400 and a significant difference in N400 activation between matching and non-matching tags.

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KW - IR-69486

KW - Multimedia tagging

KW - EEG

KW - HMI-MI: MULTIMODAL INTERACTIONS

KW - Multimedia Retrieval

KW - EWI-17167

KW - Category retrieval

KW - HMI-MR: MULTIMEDIA RETRIEVAL

KW - N400

U2 - 10.1109/ACII.2009.5349482

DO - 10.1109/ACII.2009.5349482

M3 - Conference contribution

SN - 978-1-4244-4799-2

VL - 2

SP - 27

EP - 32

BT - Proceedings 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII 2009

PB - IEEE

CY - Los Alamitos, NJ

T2 - 3rd International Conference on Affective Computing and Intelligent Interaction, ACII 2009

Y2 - 10 September 2009 through 12 September 2009

ER -

EEG analysis for implicit tagging of video data

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Keywords

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