Noise-Robust Pupil Center Detection Through CNN-Based Segmentation With Shape-Prior Loss

Noise-Robust Pupil Center Detection Through CNN-Based Segmentation With Shape-Prior Loss

Detecting the pupil center plays a key role in human-computer interaction, especially for gaze tracking. The conventional deep learning-based method for this problem is to train a convolutional neural network (CNN), which takes the eye image as the input and gives the pupil center as a regression re...

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Bibliographic Details
Main Authors: Sang Yoon Han, Hyuk Jin Kwon, Yoonsik Kim, Nam Ik Cho
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Convex shape prior
deep learning
pupil segmentation
U-Net
Online Access:https://ieeexplore.ieee.org/document/9055424/

Internet

https://ieeexplore.ieee.org/document/9055424/

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