Mastering Computer Vision with TensorFlow 2.x

Overview of 3D face detection

3D face recognition involves measuring the geometry of rigid features in the face. It is typically obtained by generating 3D images using time of flight, a range camera, or getting multiple images from a 360-degree orientation of the object. A conventional 2D camera converts a 3D space into a 2D image, which is why depth sensing is one of the fundamental challenges of computer vision. Time-of-flight-based depth estimation is based on the time it takes for a light pulse to travel from a light source to the object and back to the camera. The light source and image acquisition are synchronized to get depth. Time-of-flight sensors are able to estimate full depth frames in real time. A major issue for the time of ...