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Unraveling human perception of facial aging using eye gaze
D. Yadav, N. Kohli, E. Kalsi, , , A. Noore
Published in IEEE Computer Society
Volume: 2018-June
Pages: 2221 - 2228
Continuous efforts are being made to understand human perception network with the purpose of developing enhanced computational models for vision-based tasks. In this paper, we utilize eye gaze as a medium to unravel the cues utilized by humans for the perception of facial aging. Specifically, we explore the tasks of face age estimation and age-separate face verification and analyze the eye gaze patterns of participants to understand the strategy followed by human participants. To facilitate this, eye gaze data from 50 participants is acquired using two different eye gaze trackers: Eye Tribe and GazePoint GP3. Comprehensive analysis of various eye movement metrics is performed with respect to different face parts to illustrate their relevance for age estimation and age-separated face verification tasks. © 2018 IEEE.
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JournalData powered by TypesetIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
PublisherData powered by TypesetIEEE Computer Society