Eye center localization in a facial image based on geometric shapes of iris and eyelid under natural variability
作者：
Highlights：
• We proposed semi-circular edge shape (sCES) and semi-ellipse edge shape (sEES) features for possible eye detection.
• The Hit-or-miss transform is applied to extract positive slope edge (PSE) and negative slope edge (NSE).
• A scale-space framework (SSF) is integrated with the proposed method to address the scale variations of facial images.
• A modified gradient-based method is proposed to localize eye center more precisely.
• Experimental analyses demonstrate that our method achieves state-of-the-art performance.
摘要
•We proposed semi-circular edge shape (sCES) and semi-ellipse edge shape (sEES) features for possible eye detection.•The Hit-or-miss transform is applied to extract positive slope edge (PSE) and negative slope edge (NSE).•A scale-space framework (SSF) is integrated with the proposed method to address the scale variations of facial images.•A modified gradient-based method is proposed to localize eye center more precisely.•Experimental analyses demonstrate that our method achieves state-of-the-art performance.
论文关键词：Eye detection,Eye localization,Shape analysis,Image gradients
论文评审过程：Received 14 November 2018, Revised 11 April 2019, Accepted 6 May 2019, Available online 11 May 2019, Version of Record 12 June 2019.
论文官网地址：https://doi.org/10.1016/j.imavis.2019.05.002
