• WHitepaper

    Machine Learning Approaches for Face Detection and Face Recognition

  • ML approaches, benefits and shortcomings to face detection and recognition.


    Facial detection and recognition have applications in image and video analysis ranging from security surveillance to the simple unlocking of your phone. Face detection presents complexity for machine learning due to the variability in human faces such as the presence of glasses, the orientation of the face, presence of facial hair, differences in lightning conditions and image resolution. Face recognition is an even more complex task because of the need to interpret facial features, aging, occlusion and facial expressions.


    The paper discusses various Machine Learning approaches, benefits and shortcomings to face detection and recognition to support your own application development.