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Binocular Gaze Detection Method Using a Fuzzy Algorithm Based on Quality Measurements
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- Authors
- Chul Woo Cho, Hyeon Chang Lee, Su Yeong Gwon, Jong Man Lee, Dongwook Jung, Kang Ryoung Park, Hyun-Cheol Kim, Jihun Cha
- Issue Date
- 2014-05
- Citation
- Optical Engineering, v.53, no.5, pp.1-22
- ISSN
- 0091-3286
- Publisher
- SPIE
- Language
- English
- Type
- Journal Article
- Project Code
- 14MR9400, Development of Object-based Knowledge Convergence Service Platform using Image Recognition in Broadcasting Contents, Cho Kee Seong
- Abstract
- Due to the limitations of gaze detection based on one eye, binocular gaze detection using the gaze positions of both eyes has been researched. Most previous binocular gaze detection research calculated a gaze position as the simple average position of the detected gaze points of both eyes. To improve this approach, we propose a new binocular gaze detection method using a fuzzy algorithm with quality measurement of both eyes. The proposed method is used in the following three ways. First, in order to combine the gaze points of the left and right eyes, we measure four qualities on both eyes: distortion by an eyelid, distortion by the specular reflection (SR), the level of circularity of the pupil, and the distance between the pupil boundary and the SR center. Second, in order to obtain a more accurate pupil boundary, we compensate the distorted boundary of a pupil by an eyelid based on information from the lower half-circle of the pupil. Third, the final gaze position is calculated using a fuzzy algorithm based on four quality-measured scores. Experimental results show that the root-mean-square error of gaze estimation by the proposed method is approximately 0.67518 deg. © The Authors.
- KSP Keywords
- Detection Method, Fuzzy Algorithm, Gaze Estimation, Quality Measurement, Root mean square(RMS), Simple average, gaze detection, mean square error(MSE), root mean square error, specular reflection