Homography-Based Low-Cost Gaze Estimation and its Application to the Usability Assessment of Digital Prototypes of Information Appliances

2013 ◽  
Author(s):  
Satoshi Kanai ◽  
Hiroaki Date
Keyword(s):  
Low Cost ◽  
Test Session ◽  
Gaze Estimation ◽  
Ui Design ◽  
The Gaze ◽  
Usability Assessment ◽  
Simple Event ◽  
Information Appliances ◽  
Estimation System ◽  
Digital Prototype

Recently 3D digital prototypes of information appliances have been proposed for efficient user acceptance tests of user-interface (UI) usability. The purpose of this research is to develop a gaze estimation system based on Homography and to fully integrate it with a 3D digital prototype of the information appliances in order to obtain information more useful for usability assessment. The estimation system consists only of four infrared LEDs and a USB camera and is low-cost. The gaze estimation enables the system not only to record a gaze point on the prototype but to identify the UI objects which the user is looking for in real time during the test session. A gaze-based index was newly introduced to identify the misleading UI objects and to quantify the irrelevance of the UI design. A case study suggested that the integration of the gaze estimation with the 3D digital prototype and the proposed index were useful for automatically identifying which irrelevant UI objects misled the users’ operations which could not yet be captured in previous simple event logging of the user inputs.

scholarly journals A New Gaze Estimation Method Based on Homography Transformation Derived from Geometric Relationship

2020 ◽  
Vol 10 (24) ◽  
pp. 9079
Author(s):  
Kaiqing Luo ◽  
Xuan Jia ◽  
Hua Xiao ◽  
Dongmei Liu ◽  
Li Peng ◽  
...  
Keyword(s):  
Estimation Method ◽  
Gaze Estimation ◽  
Estimation Model ◽  
Experimental Accuracy ◽  
Unknown Parameters ◽  
The Gaze ◽  
Marquardt Algorithm ◽  
Mapping Equation ◽  
Estimation System ◽  
Homography Transformation

In recent years, the gaze estimation system, as a new type of human-computer interaction technology, has received extensive attention. The gaze estimation model is one of the main research contents of the system. The quality of the model will directly affect the accuracy of the entire gaze estimation system. To achieve higher accuracy even with simple devices, this paper proposes an improved mapping equation model based on homography transformation. In the process of experiment, the model mainly uses the “Zhang Zhengyou calibration method” to obtain the internal and external parameters of the camera to correct the distortion of the camera, and uses the LM(Levenberg-Marquardt) algorithm to solve the unknown parameters contained in the mapping equation. After all the parameters of the equation are determined, the gaze point is calculated. Different comparative experiments are designed to verify the experimental accuracy and fitting effect of this mapping equation. The results show that the method can achieve high experimental accuracy, and the basic accuracy is kept within 0.6∘. The overall trend shows that the mapping method based on homography transformation has higher experimental accuracy, better fitting effect and stronger stability.

scholarly journals CNN-Based Pupil Center Detection for Wearable Gaze Estimation System

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Warapon Chinsatit ◽  
Takeshi Saitoh
Keyword(s):  
Medical Diagnosis ◽  
Good Accuracy ◽  
Detection Method ◽  
Input Image ◽  
Classification Model ◽  
Gaze Estimation ◽  
The Gaze ◽  
Pupil Center ◽  
Center Position ◽  
Estimation System

This paper presents a convolutional neural network- (CNN-) based pupil center detection method for a wearable gaze estimation system using infrared eye images. Potentially, the pupil center position of a user’s eye can be used in various applications, such as human-computer interaction, medical diagnosis, and psychological studies. However, users tend to blink frequently; thus, estimating gaze direction is difficult. The proposed method uses two CNN models. The first CNN model is used to classify the eye state and the second is used to estimate the pupil center position. The classification model filters images with closed eyes and terminates the gaze estimation process when the input image shows a closed eye. In addition, this paper presents a process to create an eye image dataset using a wearable camera. This dataset, which was used to evaluate the proposed method, has approximately 20,000 images and a wide variation of eye states. We evaluated the proposed method from various perspectives. The result shows that the proposed method obtained good accuracy and has the potential for application in wearable device-based gaze estimation.

scholarly journals Real-time gaze estimation via pupil center tracking

2018 ◽  
Vol 9 (1) ◽  
pp. 6-18 ◽  
Author(s):  
Dario Cazzato ◽  
Fabio Dominio ◽  
Roberto Manduchi ◽  
Silvia M. Castro
Keyword(s):  
Real Time ◽  
Learning Algorithm ◽  
Natural Environments ◽  
Gaze Estimation ◽  
Head Pose ◽  
Data Set ◽  
Gaze Tracking ◽  
Illumination Changes ◽  
Wide Range ◽  
Estimation System

Abstract Automatic gaze estimation not based on commercial and expensive eye tracking hardware solutions can enable several applications in the fields of human computer interaction (HCI) and human behavior analysis. It is therefore not surprising that several related techniques and methods have been investigated in recent years. However, very few camera-based systems proposed in the literature are both real-time and robust. In this work, we propose a real-time user-calibration-free gaze estimation system that does not need person-dependent calibration, can deal with illumination changes and head pose variations, and can work with a wide range of distances from the camera. Our solution is based on a 3-D appearance-based method that processes the images from a built-in laptop camera. Real-time performance is obtained by combining head pose information with geometrical eye features to train a machine learning algorithm. Our method has been validated on a data set of images of users in natural environments, and shows promising results. The possibility of a real-time implementation, combined with the good quality of gaze tracking, make this system suitable for various HCI applications.

scholarly journals A Portable Fuzzy Driver Drowsiness Estimation System

Sensors ◽  
2020 ◽  
Vol 20 (15) ◽  
pp. 4093
Author(s):  
Alimed Celecia ◽  
Karla Figueiredo ◽  
Marley Vellasco ◽  
René González
Keyword(s):  
Real Time ◽  
Traffic Accidents ◽  
Fuzzy Inference ◽  
Low Cost ◽  
Raspberry Pi ◽  
Inference System ◽  
Visual Occlusion ◽  
Computational Performance ◽  
Estimation System ◽  
Definition Of

The adequate automatic detection of driver fatigue is a very valuable approach for the prevention of traffic accidents. Devices that can determine drowsiness conditions accurately must inherently be portable, adaptable to different vehicles and drivers, and robust to conditions such as illumination changes or visual occlusion. With the advent of a new generation of computationally powerful embedded systems such as the Raspberry Pi, a new category of real-time and low-cost portable drowsiness detection systems could become standard tools. Usually, the proposed solutions using this platform are limited to the definition of thresholds for some defined drowsiness indicator or the application of computationally expensive classification models that limits their use in real-time. In this research, we propose the development of a new portable, low-cost, accurate, and robust drowsiness recognition device. The proposed device combines complementary drowsiness measures derived from a temporal window of eyes (PERCLOS, ECD) and mouth (AOT) states through a fuzzy inference system deployed in a Raspberry Pi with the capability of real-time response. The system provides three degrees of drowsiness (Low-Normal State, Medium-Drowsy State, and High-Severe Drowsiness State), and was assessed in terms of its computational performance and efficiency, resulting in a significant accuracy of 95.5% in state recognition that demonstrates the feasibility of the approach.

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