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Semi-automatic annotation of images using eye gaze data (SAIGA)

Publication Type : Conference Proceedings

Publisher : Advances in Intelligent Systems and Computing

Source : Advances in Intelligent Systems and Computing, Springer Verlag, Volume 815, p.175-185 (2019)

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057099220&doi=10.1007%2f978-981-13-1580-0_17&partnerID=40&md5=88994d3c222ec5f54043bca7dffc0146

ISBN : 9789811315794

Keywords : Artificial intelligence, Computer interaction, Ease-of-use, Effective medium, Eye gaze tracking, eye movements, Eye Tracking, Human computer interaction, image analysis, Image annotation, Image rankings, Manual annotation, SAIGA, Semi-automatic annotation

Campus : Bengaluru

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Year : 2019

Abstract : Eye gaze tracking is based on pupil movement and is an effective medium for human–computer interaction. This field is utilized in several ways and is gaining popularity due to its increased ease of use and improved accuracy. The main objective of this paper is to present a framework that would assuage the burden of image annotations and make it more interactive. Images are annotated by physically describing their metadata. The current system gives the user 100% freedom to label the images at his/her discretion but is very tedious and time consuming. Here, we propose semi-automatic annotation of images using eye gaze data (SAIGA), an approach that would assist in using the eye gaze data to annotate images. SAIGA—the proposed framework shows how time and physical efforts spent on manual annotation can be bettered by a large value. © Springer Nature Singapore Pte Ltd. 2019.

Cite this Research Publication : B. Gottimukkala, Praveen, M. P., P. Amruta, L., and Amudha J., “Semi-automatic annotation of images using eye gaze data (SAIGA)”, Advances in Intelligent Systems and Computing, vol. 815. Springer Verlag, pp. 175-185, 2019.

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