Pupil Center Localization Based on Intensity and Image Gradient
Pupil center is a precise parameter in eye tracking,face recognition and other computer vision fields,and the realization of automatic pupil center detection has a wide range of application value.Combined with the Faster RCNN model,this study proposes a pupil localization algorithm for the human eye based on the segmented iris shape features and the image gradient method.First,the image is preprocessed with light compensation,and on this basis,the improved ResNet50 is used as the backbone network of the Faster RCNN model to detect the face and eyes.Then,the eye region is selected by geometric constraints,the iris region is detected by the integral image method,and finally the pupil center is localized by the image gradient algorithm.The experimental results show that the algorithm can achieve pupil center localization accurately on the GI4E dataset and the self-built facial dataset,and achieves 100%and 99.46%localization accuracies within the normalized error threshold of 0.2,respectively,with good robustness and real-time performance.
pupil center localizationFaster RCNNimage gradientResNet50integral image
NETL
NSTL
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