@inbook{4001854c353948aa929afd89154319a3,
title = "An EEG-based image annotation system",
abstract = "The success of deep learning in computer vision has greatly increased the need for annotated image datasets. We propose an EEG (Electroencephalogram)-based image annotation system. While humans can recognize objects in 20–200 ms, the need to manually label images results in a low annotation throughput. Our system employs brain signals captured via a consumer EEG device to achieve an annotation rate of up to 10 images per second. We exploit the P300 event-related potential (ERP) signature to identify target images during a rapid serial visual presentation (RSVP) task. We further perform unsupervised outlier removal to achieve an F1-score of 0.88 on the test set. The proposed system does not depend on category-specific EEG signatures enabling the annotation of any new image category without any model pre-training.",
keywords = "Active learning, EEG, Image annotation",
author = "Viral Parekh and Ramanathan Subramanian and Dipanjan Roy and Jawahar, {C. V.}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2018. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.; 6th National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics, NCVPRIPG 2017 ; Conference date: 16-12-2017 Through 19-12-2017",
year = "2018",
doi = "10.1007/978-981-13-0020-2_27",
language = "English",
isbn = "9789811300196",
volume = "Netherlands",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "303--313",
editor = "Renu Rameshan and {Dutta Roy}, Sumantra and Chetan Arora",
booktitle = "Computer Vision, Pattern Recognition, Image Processing, and Graphics - 6th National Conference, NCVPRIPG 2017, Revised Selected Papers",
address = "Netherlands",
}