Apr 7, 2021 · When drivers shift their eyes without turning their heads to look at objects, the margin of error in gaze detection increases. For new consumer electronic applications such as …

The data source is Kaggle's Gaze-Eye Detection dataset, which contains eye-region images categorized by gaze directions in labeled folders. Each image is pre-labeled to indicate actual …

A novel approach to critical parts of face detection problems is given, based on analogic cellular neural network (CNN) algorithms. The proposed CNN algorithms find and help to normalize …

Abstract—An eye detection algorithm based on Convolutional Neural Networks (CNN) architecture was developed. The algorithm was designed to detect eyes in video images from …

Summarize the given pdf see discussions, stats, and author profiles for this publication at: convolutional neural networks (cnn) based tracking system using

Common eye tracking algorithms use infrared LEDs shown onto the eye, then compute the relative distance of that light to the pupil of the eye as a means to determine eye movement. …

We gather information about the location of the eyes in each image based on the head position. In this article, we present a method for estimating eye direction based on convolutional neural …

l computational requirements is introduced and assessed for efficient appearance-based gaze estimation. The model is tested and compared against existing appearance based CNN …

In this project, we explore how to make use of a machine learning approach to detection the eye gaze, which is represented by 7 directions including upper left, upper right, left, right, lower left, …

May 2, 2021 · This work also includes pre-trained models, network structures, and datasets for designing and developing CNN-based deep learning models for Eye-Gaze Tracking and …