CPC G06T 17/00 (2013.01) [G06N 3/08 (2013.01); G06Q 30/0269 (2013.01); G06T 3/40 (2013.01); G06T 7/11 (2017.01); G06T 19/006 (2013.01); G06V 10/454 (2022.01); G06V 10/82 (2022.01); G06V 20/64 (2022.01); G06V 40/16 (2022.01); G06V 40/161 (2022.01); G06V 40/171 (2022.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01)] | 13 Claims |
1. A two-dimensional (2D) image processing method comprising:
obtaining a 2D image;
processing the obtained 2D image by using a trained convolutional neural network (CNN) to obtain at least one camera parameter, at least one face model parameter and at least one emotion parameter from the 2D image;
generating a three-dimensional (3D) face model, based on the obtained at least one camera parameter and at least one face model parameter;
determining a feeling of a user by using the obtained at least one emotion parameter; and
providing an advertisement of a product or service, based on the determined feeling of the user,
wherein the obtained at least one emotion parameter is based on predefined landmarks of the 2D image compared to a 3D morphable face model, and
wherein the processing of the 2D image by using the trained CNN comprises:
adjusting a size of the 2D image,
detecting a face from the size-adjusted 2D image,
indicating, with a bounding box, a face region comprising the detected face,
cutting an image of the face region indicated by the bounding box, from the 2D image,
generating a second image by adjusting a size of the cut image of the face region,
marking at least one landmark of the face on the second image, and
obtaining at least one camera parameter and at least one face model parameter that most closely match the at least one landmark.
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