scholarly journals Development of an Eye Tracking-Based Human-Computer Interface for Real-Time Applications

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3630 ◽  
Author(s):  
Radu Gabriel Bozomitu ◽  
Alexandru Păsărică ◽  
Daniela Tărniceriu ◽  
Cristian Rotariu
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Detection Rate ◽  
Detection Algorithm ◽  
Computer Interface ◽  
Human Computer Interface ◽  
Detection Techniques ◽  
Scene Image ◽  
Real Time Applications ◽  
Circular Target

In this paper, the development of an eye-tracking-based human–computer interface for real-time applications is presented. To identify the most appropriate pupil detection algorithm for the proposed interface, we analyzed the performance of eight algorithms, six of which we developed based on the most representative pupil center detection techniques. The accuracy of each algorithm was evaluated for different eye images from four representative databases and for video eye images using a new testing protocol for a scene image. For all video recordings, we determined the detection rate within a circular target 50-pixel area placed in different positions in the scene image, cursor controllability and stability on the user screen, and running time. The experimental results for a set of 30 subjects show a detection rate over 84% at 50 pixels for all proposed algorithms, and the best result (91.39%) was obtained with the circular Hough transform approach. Finally, this algorithm was implemented in the proposed interface to develop an eye typing application based on a virtual keyboard. The mean typing speed of the subjects who tested the system was higher than 20 characters per minute.

Real time vision-based hand gesture estimation for a human-computer interface

1997 ◽  
Vol 28 (7) ◽  
pp. 76-88 ◽  
Author(s):  
Koichi Ishibuchi ◽  
Keisuke Iwasaki ◽  
Haruo Takemura ◽  
Fumio Kishino
Keyword(s):  
Real Time ◽  
Computer Interface ◽  
Hand Gesture ◽  
Human Computer Interface

Metadata-driven eye tracking for real-time applications

2021 ◽  
Author(s):  
Yasith Jayawardana ◽  
Gavindya Jayawardena ◽  
Andrew T. Duchowski ◽  
Sampath Jayarathna
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Real Time Applications

The Calibration & Monitor System of Battery Operation Parameters Simulation Generator Based on LabVIEW

2013 ◽  
Vol 645 ◽  
pp. 272-275 ◽  
Author(s):  
Jie Zeng ◽  
Li Jiang ◽  
Yuan Ma
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Virtual Instrument ◽  
Computer Interface ◽  
Battery Management ◽  
Human Computer Interface ◽  
Online Data ◽  
Management Units ◽  
Time Calibration ◽  
Operation Parameters

A battery operation parameters simulation generator was specially designed for testing battery management units. Its purpose is to provide a test platform for the industrialization of the battery management units. The parameters simulation generator can provide the battery in various conditions of voltage, current, temperature and other analog signals. In order to calibrate the battery simulation parameters in real-time, a complete set of the calibration and monitoring interface was designed based on LabVIEW (Laboratory Virtual Instrument Engineering Workbench) environment. The human-computer interface can achieve calibration control of voltage, current, temperature signals online, data analysis, data display, data storage, and fault diagnosis. Test results show that the developed human-computer interface is able to realize real-time calibration and monitoring functions for battery operation parameters simulation generator. Furthermore，the interface also has good real-time and stability, and has a certain application value on the testing and evaluation of the battery management unit.

scholarly journals AUTOMATIC EYE TEMPLATE GENERATION AND TRACKING

2014 ◽  
pp. 226-230
Author(s):  
RICHA MEHTA ◽  
MANISH SHRIVASTAVA
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Facial Feature ◽  
Detection Algorithm ◽  
Eye Blink ◽  
Eye Blinks ◽  
The Road ◽  
Blink Detection ◽  
Two Phases ◽  
Real World Problems

Eye blinking is a physiological necessity for humans. This method automatically locates the user’s eye by detecting eye blinks. A system is the improvement of driver carefulness and accident reduction. The driver’s face is tracked while he is driving and he is warned if there seems to be an alerting fact that can result in an accident such as sleepy eyes, or looking out of the road. Furthermore, with a facial feature tracker, it becomes possible to play a synthesized avatar so that it imitates the expressions of the performer. For a user who is incapable of using her hands, a facial expression controller may be a solution to send limited commands to a computer. Eye blinking is one of the prominent areas to solve many real world problems. The process of blink detection consists of two phases. These are eye tracking followed by detection of blink. The work that has been carried out for eye tracking only is not suitable for eye blink detection. Therefore some approaches had been proposed for eye tracking along with eyes blink detection. In this thesis, real time implementation is done to count number of eye blinks in an image sequence. At last after analyzing all these approaches some of the parameters we obtained on which better performance of eye blink detection algorithm depend. This project focuses on automatic eye blink detection in real time. The aim of this thesis is to count the number of eye blinks in a video. This project will be performed on a video database of the facial expressions.

Convolutional Neural Networks for Real-Time Eye Tracking in Interactive Applications

2021 ◽  
pp. 455-473
Author(s):  
Michael Burch ◽  
Andrei Jalba ◽  
Carl van Dueren den Hollander
Keyword(s):  
Eye Tracking ◽  
Real Time ◽  
Network Architecture ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Face Alignment ◽  
Interactive Applications ◽  
Processing Power ◽  
Real Time Applications ◽  
Pose Alignment

Face alignment and eye tracking for interactive applications should be performed with very low latency or users will notice the delay. In this chapter, a face alignment method for real-time applications is introduced featuring a convolutional neural network architecture for face and pose alignment. The performance of the novel method is compared to a face alignment algorithm included in the freely available OpenFace toolkit, which also focuses on real-time applications. The approach exceeds OpenFace's performance on both our own and the 300W test sets in terms of accuracy and robustness but requires significant parallel processing power, currently provided by the GPU. For the eye tracking application, stereo cameras are used as input to determine the position of a user's eyes in three-dimensional space. It does not require synchronized recordings, which may contain redundant information, and instead prefers staggered recordings, which maximize the number of possible model updates.

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