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This repo contains implementation of CNN based regression network for Pupil Center Estimation in smartphones

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soumilchugh/PupilCenterEstimation

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CNN Architecture for Pupil Center Estimation in eye images extracted from head tracker of a smartphone

*5 Convolutional Layers with a stride of 1 and 3x3 filters

  • 1 Fully Connected Layer with 2048 units
  • Average Pooling of 2x2 with a stride of 2
  • Batch Normalization and Dropout after every layer
  • Loss Function – Euclidean Distance between true and predicted labels

Raw images of the pupil obtained from a infrared camera in a smartphone along with their histograms

Result of applying different image enhancement techniques such as Histogram Equalisation, Power Law, Adaptive Histogram Equalisation

  • Adaptive Histogram Equalisation

* Power Law

* Histogram Equalisation

* Adaptive Histogram Equalisation plus Power Law

Mean Pixel Error after training on the same dataset but with different image enhancement techniques

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