Laddi, Amit and Prakash, N.R. (2016) An augmented image gradients based supervised regression technique for iris center localization. Multimedia Tools and Applications. pp. 1-11. ISSN 1380-7501
Full text not available from this repository.Abstract
This paper describes a robust and accurate technique for iris center localization by combining supervised regression based approach and image gradients. The proposed work consist of two stages. The first stage comprises regression approach which is based upon learning of local binary features to detect the periocular regions. In the second stage, image gradients were applied to the extracted eye patch regions to detect the accurate iris centers. The proposed augmented image gradients based supervised regression approach tested on the two publicly available challenging datasets show good accuracy. The results proved that supervised regression technique when augmented with image gradients approach improved the accuracy of iris center detection on the face image acquired under unconstraint conditions. The outcome of the proposed work suggests that by augmenting effective unsupervised techniques such as image gradients improves the accuracy and robustness of the supervised approaches used for face alignment applications. This work may be extended towards the development of accurate and fast eye gaze tracking systems.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Supervised; Regression; Gradients; Iris centers; Eye gaze |
| Subjects: | CSIO > Medical Instrumentation |
| Divisions: | Medical Instrumentation |
| Depositing User: | Ms. Jyotsana |
| Date Deposited: | 09 Aug 2018 11:58 |
| Last Modified: | 09 Aug 2018 11:58 |
| URI: | http://csioir.csio.res.in/id/eprint/621 |
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