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. 2022 Nov 29;10(12):2396. doi: 10.3390/healthcare10122396
Algorithm 1 Face detection procedures
Input: Original image
Output: The image with only the face
  •   1:

    Set the environment variables to match the features of the face.

  •   2:

    Adjust the image to fit the requirements.

  •   3:

    Pass the processed image into ResNet-101 and obtain the corresponding feature map.

  •   4:

    FPN corrects the size of the RoIs in the feature map.

  •   5:

    RPN classifies these RoIs and filters out the background, and BB regression corrects the BB of the RoI.

  •   6:

    Use RoI alignment to split the remaining RoIs into facial RoIs and non-facial RoIs.

  •   7:

    Use BB Regression to fix the BB of RoI again and generate the mask with FCN after classification.

  •   8:

    Keep the facial part after the non-facial part becomes black.

  •   9:

    End.