Computational Intelligence and Neuroscience / 2015 / Article / Tab 2

Research Article

An Efficient Robust Eye Localization by Learning the Convolution Distribution Using Eye Template

Table 2

Comparison of accuracies among the state-of-the-art eye localization approaches. Note the robust algorithms with high accuracies on LFPW.

Method Accuracy Mean error
BioID LFPW BioID LFPW
Right eye Left eye Right eye Left eye Right eye Left eye Right eye Left eye

Our method 98.1% 98.2% 96.8%96.9%2.7%2.4%3.4%3.1%
Deep CNN 99.9%100%99.1%99.4%1.7%1.5%2.1%2.0%
ASEF 1.2% 0.2% 2.4% 0.6% 121.4% 88% 81.2% 99.2%
nu-SVR 96.1% 95.9% 92.8% 92.8% 4.2% 4.1% 4.9% 4.9%
BORMAN 79.1% 75.8% 78.2% 92.8% 7.1% 7.8% 7.8% 8.8%
CBDS 97.7% 98.9% 87.9% 91.9% 4.1% 3.9% 7.2% 7%
LUXAND 98.9% 98.66% 95.6% 96.8% 4.1% 3.7% 5.6% 4.5%