Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/2557
Title: | A Low Rank Model Based Improved Eye Detection Under Spectacles |
Authors: | Lazarus, M Z Gupta, S |
Keywords: | Eye detection Low rank model Spectacle reflection Glare removal |
Issue Date: | Oct-2016 |
Publisher: | IEEE |
Citation: | IEEE 7th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON),Columbia University, New York, USA, 20-22 October 2016 |
Abstract: | Eye detection is a primary step in many applications such as face recognition, iris recognition, driver fatigue detection, gaze tracking etc. Occlusion by spectacles, glare and secondary image formations deteriorate its performance. In this paper, we formulate the glare/reflection removal as a classification problem and employ Low rank decomposition technique to overcome these challenges. We provide an in-depth analysis by comparing various low rank decomposition formulations and propose a simple preprocessing step to improve the detection accuracy. Experimentation on CASIA NIR-VIS 2.0 facial database validates the proposed preprocessing method. |
Description: | Copyright belongs to the proceeding publisher |
URI: | http://hdl.handle.net/2080/2557 |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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2016_IEE_UEMCON_PID4467077_SGupta.pdf | 734.76 kB | Adobe PDF | View/Open |
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