Error Analysis of Line of Sight Estimation using Purkinje Images for Eye-based Human-Computer Interaction: HCI
Journal Title: International Journal of Advanced Research in Artificial Intelligence(IJARAI) - Year 2016, Vol 5, Issue 10
Abstract
Error analysis of line of sight estimation using Purkinje images for eye-based Human-Computer Interaction: HCI is conducted. Double Purkinje images which are obtained by two points of light sources are used in the proposed method for eye rotation angle estimation. It aimed at the improvement of the eyeball rotation angle accuracy by simply presuming the value of the curvature radius of the cornea. This technique is a cancellation of the time of the calibration that is the problem of past glance presumption. By presuming the size of the radius of curvature of the cornea. As a result, the eyeball rotation angle presumption accuracy of about 0.98deg was obtained 0.57deg and horizontally in the vertical direction without doing the calibration.
Authors and Affiliations
Kohei Arai
Keywords
Related Articles
- EP ID EP164832
- DOI 10.14569/IJARAI.2016.051003
- Views 100
- Downloads 0
Prediction of New Student Numbers using Least Square Method
STMIK BANJARBARU has acquired less number of new students for the last three years compared to the previous years. The numbers of new student acquisition are not always the same every year. The unstable number of n...
An Intelligent Location Management approaches in GSM Mobile Network
Location management refers to the problem of updating and searching the current location of mobile nodes in a wireless network. To make it efficient, the sum of update costs of location database must be minimized. Previo...
Improved Fuzzy C-Mean Algorithm for Image Segmentation
The segmentation of image is considered as a significant level in image processing system, in order to increase image processing system speed, so each stage in it must be speed reasonably. Fuzzy c-mean clustering i...
Comparative Analysis of Improved Cuckoo Search(ICS) Algorithm and Artificial Bee Colony (ABC) Algorithm on Continuous Optimization Problems
This work is related on two well-known algorithm, Improved Cuckoo Search and Artificial Bee Colony Algorithm which are inspired from nature. Improved Cuckoo Search (ICS) algorithm is based on Lévy flight and behavi...
Density Based Support Vector Machines for Classification
Support Vector Machines (SVM) is the most successful algorithm for classification problems. SVM learns the decision boundary from two classes (for Binary Classification) of training points. However, sometimes there...