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.