Unraveling Human Perception of Facial Aging Using Eye Gaze

Daksha Yadav, Naman Kohli, Ekampreet Kalsi, Mayank Vatsa, Richa Singh, Afzel Noore; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018, pp. 2140-2147

Abstract


Continual 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.

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[bibtex]
@InProceedings{Yadav_2018_CVPR_Workshops,
author = {Yadav, Daksha and Kohli, Naman and Kalsi, Ekampreet and Vatsa, Mayank and Singh, Richa and Noore, Afzel},
title = {Unraveling Human Perception of Facial Aging Using Eye Gaze},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2018}
}