Eye tracking apparatus and method thereof

1. An eye tracking apparatus, comprising:

an image capture device, configured to capture at least one face image; and

a computing device, coupled to the image capture device, receiving the face image to obtain an eye image, performing an image enhancing operation to enhance the eye image and thereby generate an enhanced eye image, and defines the at least one iris region in the enhanced eye image, identifying at least one iris region in the eye image, and choosing a largest iris region from a plurality of fitting patterns based on calculated radii of the plurality of fitting patterns; wherein a gaze point of the eye is a center of the fitting patterns,

a training device, coupled to the computing device and configured to perform a training operation on an eye image sample to generate a classification parameter; and

a storage device, coupled to the training device and the computing device, and configured to store the classification parameter, such that the computing device identifies the at least one iris region in the eye image based on the classification parameter.

2. The eye tracking apparatus as claimed in claim 1 , wherein the image enhancing operation comprises an image brightness adjustment operation, an image contrast increment operation and/or a Weickert image enhancing operation.

3. The eye tracking apparatus as claimed in claim 2 , wherein the image brightness adjustment comprises increasing a brightness at a position with an excessively low grayscale value in the eye image.

4. The eye tracking apparatus as claimed in claim 2 , wherein the image brightness adjustment comprises lowering a brightness at a position with an excessively high grayscale value in the eye image.

5. The eye tracking apparatus as claimed in claim 1 , wherein the training operation comprises model training based on multi-layer neural networks.

6. The eye tracking apparatus as claimed in claim 1 , wherein the computing device defines the at least one iris region in the enhanced eye image based on the classification parameter.

7. The eye tracking apparatus as claimed in claim 1 , wherein the computing device masks the enhanced eye image.

8. The eye tracking apparatus as claimed in claim 1 , wherein the computing device classifies the eye image into the largest iris region and a non-iris region.

9. The eye tracking apparatus as claimed in claim 8 , wherein the non-iris region comprises a first sclera region and a second sclera region assisting to position the largest iris region.

10. The eye tracking apparatus as claimed in claim 1 , further comprising:

a display device, coupled to the computing device and configured to display an output response based on the gaze point.

11. The eye tracking apparatus as claimed in claim 1 , wherein the plurality of fitting patterns are minimum covering circles or minimum covering ellipses.

12. An eye tracking method, comprising:

capturing at least one face image;

obtaining an eye image of the face image;

performing a training operation on an eye image sample to obtain a classification parameter;

storing the classification parameter;

identifying the at least one iris region in the eye image based on the classification parameter;

performing an image enhancing operation to enhance the eye image and thereby generate an enhanced eye image, and defines the at least one iris region in the enhanced eye image;

identifying at least one iris region with irregular shapes in the eye image;

choosing a largest iris region from the at least one iris region and obtaining a plurality of fitting patterns of the largest iris region with the largest calculated radii from a plurality of fitting patterns; and

obtaining a gaze point of the eye image based on a center of the fitting patterns.

13. The eye tracking method as claimed in claim 12 , wherein the step of enhancing the eye image to generate the enhanced eye image comprises an image brightness adjustment operation, an image contrast increment operation and/or a Weickert image enhancing operation.

14. The eye tracking method as claimed in claim 13 , wherein the image brightness adjustment comprises increasing a brightness at a position with an excessively low grayscale value in the eye image.

15. The eye tracking method as claimed in claim 14 , wherein the image brightness adjustment comprises lowering a brightness at a position with an excessively high grayscale value in the eye image.

16. The eye tracking method as claimed in claim 12 , wherein the training operation comprises model training based on multi-layer neural networks.

17. The eye tracking method as claimed in claim 12 , wherein identifying the at least one iris region in the eye image comprises: identifying the at least one iris region in the enhanced eye image based on the classification parameter.

18. The eye tracking method as claimed in claim 12 , wherein identifying the at least one iris region in the eye image further comprises:

masking the enhanced eye image.

19. The eye tracking method as claimed in claim 12 , wherein choosing the largest iris region from the at least one iris region and obtaining the fitting pattern of the largest iris region comprises:

classifying the eye image into the largest iris region and a non-iris region.

20. The eye tracking method as claimed in claim 19 , wherein the non-iris region comprises a first sclera region and a second sclera region assisting to position the largest iris region.

21. The eye tracking method as claimed in claim 12 , further comprising:

displaying a output response based on the gaze point.

22. The eye tracking apparatus as claimed in claim 12 , wherein the plurality of fitting patterns are minimum covering circles or minimum covering ellipses.