Paper Info
Title
A new low-cost eye tracking and blink detection approach: extracting eye features with blob extraction
Abstract
The systems let user track their eye gaze information have been technologically possible for several decades. However, they are still very expensive. They have limited use of eye tracking and blink detection infra-structure. The purpose of this paper is to evaluate cost effects in the sector and explain our new approach in detail which reduces high costs of current systems apparently. This paper introduces an algorithm for fast and sub-pixel precise detection of eye blobs for extracting eye features. The algorithm is based on differential geometry and still exists in OpenCpV library as a class. Hence, blobs of arbitrary size that means eye size can be extracted by just adjusting the scale parameter in the class function. In addition, center point and boundary of an eye blob, also are extracted. These describe the specific eye location in the face boundary to run several algorithms to find the eye-ball location with its central coordinates. Several examples on real simple web-cam images illustrate the performance of the proposed algorithm and yield an efficient result on the idea of low-cost eye tracking, blink detection and drowsiness detection system.
Year
Venue
Keywords
2009
ICIC (1)
drowsiness detection system,eye feature,new low-cost eye tracking,specific eye location,low-cost eye tracking,blink detection,detection infra-structure,eye size,sub-pixel precise detection,detection approach,eye tracking,eye blob,blob extraction,cost effectiveness,eye gaze,differential geometry
Field
DocType
Volume
Blink detection,Computer vision,Pattern recognition,Class function,Computer science,Eye tracking,Differential geometry,Artificial intelligence,Scale parameter
Conference
5754
ISSN
ISBN
Citations 
0302-9743
3-642-04069-1
3
PageRank 
References 
Authors
0.43
11
2
Name
Order
Citations
PageRank
Ibrahim Furkan Ince1134.13
Tae-Cheon Yang2323.71