This code accompanies the article titled "Framework for Posture and Face Recognition Using Kinect an Ambient-intelligence Method" by Liviu Vladutu, Cosmin Marian, has been published in the WSEAS Transactions on Computers, ISSN / E-ISSN: 1109-2750 / 2224-2872, Volume 22, 2023, Art. #3, p.13-24: https://wseas.com/journals/computers/2023/a085105-004(2023).pdf
DOI: 10.37394/23205.2023.22.3
Face detection & recognition with OpenCV, Python and deep learning
Related links: https://towardsdatascience.com/using-linkedin-profile-pictures-for-facial-recognition-8be709e8fac
https://www.pyimagesearch.com/2018/06/18/face-recognition-with-opencv-python-and-deep-learning/
Significance of the facial landmarks is given here:
- https://pyimagesearch.com/2017/04/10/detect-eyes-nose-lips-jaw-dlib-opencv-python/
- in accordance with: https://ibug.doc.ic.ac.uk/resources/facial-point-annotations/
Setup
- Python 3.6.6+
OpenCV 4.x
Make sure OpenCV4 is installed.
Libraries
pip install dlib
pip install face_recognition
pip install imutils
Creating image encodings
You will need to run encode_faces.py
This script takes 3 parameters:
ap.add_argument("-d", "--dataset", required=False, default="/Volumes/MacBackup/friends_family", help="path to input dataset directory")
ap.add_argument("-e", "--encodings-file", required=False, default='encodings/friends_family_encodings.pkl', help="path to serialized db of facial encodings")
ap.add_argument("-m", "--detection-method", type=str, default='cnn', help="face detection model to use: either 'hog' or 'cnn' ")- dataset is the path to the root directory where subdirectories exist and contain image of people.
For example, above hte 'friends_family' contains folders like:
bob_builder
john_public
jane_doe
where each of those folders contain images of those people.
-
encoding-file is the name of the output file that contains the encodings for all of the people in the dataset directory
-
detection-method is the face finding method. If you are on a laptop or better, use 'cnn'