A Novel Eye Gaze Tracking Technique Based on Pupil Center Cornea Reflection Technique

2010 ◽  
Vol 33 (7) ◽  
pp. 1272-1285 ◽  
Author(s):  
Chuang ZHANG ◽  
Jian-Nan CHI ◽  
Zhao-Hui ZHANG ◽  
Zhi-Liang WANG
Keyword(s):  
Eye Gaze ◽  
Gaze Tracking ◽  
Pupil Center ◽  
Tracking Technique

scholarly journals PerSummRe

2022 ◽  
Vol 24 (3) ◽  
pp. 1-18
Author(s):  
Neeru Dubey ◽  
Amit Arjun Verma ◽  
Simran Setia ◽  
S. R. S. Iyengar
Keyword(s):  
Recommendation System ◽  
Information Overload ◽  
Eye Gaze ◽  
Experimental Results ◽  
User Profiling ◽  
Gaze Tracking ◽  
Non Invasive ◽  
Tracking Technique

The size of Wikipedia grows exponentially every year, due to which users face the problem of information overload. We purpose a remedy to this problem by developing a recommendation system for Wikipedia articles. The proposed technique automatically generates a personalized synopsis of the article that a user aims to read next. We develop a tool, called PerSummRe, which learns the reading preferences of a user through a vision-based analysis of his/her past reads. We use an ensemble non-invasive eye gaze tracking technique to analyze user’s reading pattern. This tool performs user profiling and generates a recommended personalized summary of yet unread Wikipedia article for a user. Experimental results showcase the efficiency of the recommendation technique.

PerSummRe

2022 ◽  
Vol 24 (3) ◽  
pp. 0-0
Keyword(s):  
Recommendation System ◽  
Information Overload ◽  
Eye Gaze ◽  
Experimental Results ◽  
User Profiling ◽  
Gaze Tracking ◽  
Non Invasive ◽  
Tracking Technique

The size of Wikipedia grows exponentially every year, due to which users face the problem of information overload. We purpose a remedy to this problem by developing a recommendation system for Wikipedia articles. The proposed technique automatically generates a personalized synopsis of the article that a user aims to read next. We develop a tool, called PerSummRe, which learns the reading preferences of a user through a vision-based analysis of his/her past reads. We use an ensemble non-invasive eye gaze tracking technique to analyze user’s reading pattern. This tool performs user profiling and generates a recommended personalized summary of yet unread Wikipedia article for a user. Experimental results showcase the efficiency of the recommendation technique.

Implementation of eye gaze tracking technique on FPGA-based on-screen keyboard system using verilog and MATLAB

2017 ◽  
Author(s):  
Dionis A. Padilla ◽  
Joseph Aaron B. Adriano ◽  
Jessie R. Balbin ◽  
Ivan G. Matala ◽  
Jan Julien R. Nicolas ◽  
...  
Keyword(s):  
Eye Gaze ◽  
Gaze Tracking ◽  
Tracking Technique

Accurate Pupil Center Location with the SIFT Descriptor and SVM Classifier

2016 ◽  
Vol 30 (04) ◽  
pp. 1655012 ◽  
Author(s):  
Zhizhi Guo ◽  
Qianxiang Zhou ◽  
Zhongqi Liu ◽  
Chunhui Liu
Keyword(s):  
Accurate Result ◽  
Eye Gaze ◽  
Support Vector ◽  
Svm Classifier ◽  
Low Resolution ◽  
Scale Invariant ◽  
Gaze Tracking ◽  
Pupil Center ◽  
Sift Descriptor ◽  
Low Resolution Images

Locating the center of the pupils is the most important foundation and the core component of gaze tracking. The accuracy of gaze tracking largely depends on the quality of images, but additional constraints and large amount of calculation make gaze tracking impractical on high-resolution images. Although some eye-gaze trackers can get accurate result, improving the accuracy of pupil feature on low-resolution images and accurately recognizing closed eye images are still common tasks in the field of gaze estimation. Our aim is to get the accurate localization of pupil center on low-resolution image. To this aim, we proposed a simple but effective method which can accurately locate pupil center in real time. The method first gets initial eye center based on improved scale-invariant feature transform (SIFT) descriptor and support vector machine (SVM) classifier, and then gets final position of the pupil center through a size variable correction rectangular block. In this paper, comparing with the reported state-of-the-art methods,the experimental results demonstrate that our system can achieve a more accurate result on low-resolution images. On top of that, our approach shows robustness on closed eye images while some other methods would not recognize the closed eye images.

A Low-Cost Pupil Center Localization Algorithm Based on Maximized Integral Voting of Circular Hollow Kernels

2018 ◽  
Vol 62 (7) ◽  
pp. 1001-1015 ◽  
Author(s):  
Ibrahim Furkan Ince ◽  
Yusuf Sait Erdem ◽  
Faruk Bulut ◽  
Md Haidar Sharif
Keyword(s):  
Processing Speed ◽  
Low Cost ◽  
Eye Gaze ◽  
Video Stream ◽  
Computational Time ◽  
Localization Algorithm ◽  
Gaze Tracking ◽  
Free System ◽  
Essential Requirement ◽  
Pupil Center

Abstract Pupil center localization is an essential requirement for robust eye gaze tracking systems. In this paper, a low-cost pupil center localization algorithm is presented. The aim is to propose a computationally inexpensive algorithm with high accuracy in terms of performance and processing speed. Hence, a computationally inexpensive pupil center localization algorithm based on maximized integral voting of candidate kernels is presented. As the kernel type, a novel circular hollow kernel (CHK) is used. Estimation of pupil center is employed by applying a rule-based schema for each pixel over the eye sockets. Additionally, several features of CHK are proposed for maximizing the probability of voting for each kernel. Experimental results show promising results with 96.94% overall accuracy with around 13.89 ms computational time (71.99 fps) for a single image as an average time by using a standard PC. An extensive benchmarking study indicates that this method outperforms the learning-free algorithms and it competes with the other methods having a learning phase while their processing speed is much higher. Furthermore, this proposed learning-free system is fast enough to run on an average PC and also applicable to work with even a low-resolution webcam on a real-time video stream.

A NOVEL INFRARED GAZE TRACKING SYSTEM BASED ON NONUNIFORM INTERPOLATION

2010 ◽  
Vol 22 (03) ◽  
pp. 185-192 ◽  
Author(s):  
Jin-Yu Chu ◽  
Jian-De Sun ◽  
Xiao-Hui Yang ◽  
Ju Liu ◽  
Wei Liu
Keyword(s):  
Tracking System ◽  
Eye Gaze ◽  
Mapping Method ◽  
Research Field ◽  
Projection Algorithm ◽  
Infrared Light ◽  
Light Sources ◽  
Gaze Tracking ◽  
Pupil Center ◽  
A Charge

The gaze tracking system has become an active research field for handicapped persons as well as general people in recent years. The precise mapping method plays an important role in the system. In this paper, a novel infrared gaze tracking system based on nonuniform interpolation is proposed. In this system, the eye images for the computer to analyze are extracted under two infrared light sources and a charge-coupled device camera, and the users do not require wearing any device. First, the integral projection algorithm and canny edge detection are applied to extract the pupil boundary points from the captured eye images, and then the pupil center is computed using an efficient and accurate ellipse-fitting algorithm. Finally, to estimate where the user looks, a novel mapping method based on the nonuniform interpolation algorithm is proposed. In this mapping method, the complicated geometric eyeball model and the nonlinear mapping between the pupil center coordinates and computer monitor screen coordinates do not need to be taken into account. Experimental results show that the proposed mapping method is simple, fast and more accurate. Moreover, our system is the remote eye gaze tracking system. The users do not need to wear any device, which make the users feel more comfortable.

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