Abstract
In multimedia content sharing social networks, tags assigned to content play an important role in search and retrieval. In other words, by annotating multimedia content, users can associate a word or a phrase (tag) with that resource such that it can be searched for efficiently. Implicit tagging refers to assigning tags by observing subjects behavior during consumption of multimedia content. This is an alternative to traditional explicit tagging which requires an explicit action by subjects. In this paper we propose a brain-computer interface (BCI) system based on P300 evoked potential, for implicit emotional tagging of multimedia content. We show that our system can successfully perform implicit emotional tagging and naïve subjects who have not participated in training of the system can also use it efficiently. Moreover, we introduce a subjective metric called "emotional taggability" to analyze the recognition performance of the system, given the degree of ambiguity that exists in terms of emotional values associated with a multimedia content.
| Original language | English |
|---|---|
| Title of host publication | 1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09 |
| Pages | 81-88 |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 2009 Dec 22 |
| Event | 1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09 - Beijing, China Duration: 2009 Oct 19 → 2009 Oct 24 |
Publication series
| Name | 1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09 |
|---|
Other
| Other | 1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 09/10/19 → 09/10/24 |
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All Science Journal Classification (ASJC) codes
- Computer Graphics and Computer-Aided Design
- Human-Computer Interaction
- Software
Cite this
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Implicit emotional tagging of multimedia using EEG signals and brain computer interface. / Yazdani, Ashkan; Lee, Jong Seok; Ebrahimi, Touradj.
1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09. 2009. p. 81-88 (1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Implicit emotional tagging of multimedia using EEG signals and brain computer interface
AU - Yazdani, Ashkan
AU - Lee, Jong Seok
AU - Ebrahimi, Touradj
PY - 2009/12/22
Y1 - 2009/12/22
N2 - In multimedia content sharing social networks, tags assigned to content play an important role in search and retrieval. In other words, by annotating multimedia content, users can associate a word or a phrase (tag) with that resource such that it can be searched for efficiently. Implicit tagging refers to assigning tags by observing subjects behavior during consumption of multimedia content. This is an alternative to traditional explicit tagging which requires an explicit action by subjects. In this paper we propose a brain-computer interface (BCI) system based on P300 evoked potential, for implicit emotional tagging of multimedia content. We show that our system can successfully perform implicit emotional tagging and naïve subjects who have not participated in training of the system can also use it efficiently. Moreover, we introduce a subjective metric called "emotional taggability" to analyze the recognition performance of the system, given the degree of ambiguity that exists in terms of emotional values associated with a multimedia content.
AB - In multimedia content sharing social networks, tags assigned to content play an important role in search and retrieval. In other words, by annotating multimedia content, users can associate a word or a phrase (tag) with that resource such that it can be searched for efficiently. Implicit tagging refers to assigning tags by observing subjects behavior during consumption of multimedia content. This is an alternative to traditional explicit tagging which requires an explicit action by subjects. In this paper we propose a brain-computer interface (BCI) system based on P300 evoked potential, for implicit emotional tagging of multimedia content. We show that our system can successfully perform implicit emotional tagging and naïve subjects who have not participated in training of the system can also use it efficiently. Moreover, we introduce a subjective metric called "emotional taggability" to analyze the recognition performance of the system, given the degree of ambiguity that exists in terms of emotional values associated with a multimedia content.
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UR - http://www.scopus.com/inward/citedby.url?scp=72149117092&partnerID=8YFLogxK
U2 - 10.1145/1631144.1631160
DO - 10.1145/1631144.1631160
M3 - Conference contribution
AN - SCOPUS:72149117092
SN - 9781605587592
T3 - 1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09
SP - 81
EP - 88
BT - 1st ACM SIGMM International Workshop on Social Media, WSM'09, Co-located with the 2009 ACM International Conference on Multimedia, MM'09
ER -