In recent years, artificial intelligence has demonstrated tremendous potential for the development and advancement of a wide variety of technologies. A good example is facial direction estimation, which finds applications .
In recent years, artificial intelligence has demonstrated tremendous potential for the development and advancement of a wide variety of technologies. A good example is facial direction estimation, which finds applications in driver assistance systems that prevent distracted driving, methods to prevent cheating in examinations, and software for creating three-dimensional (3D) virtual avatars.
Traditional facial orientation estimation techniques recognize the characteristic parts of the face, including the nose, eyes, and mouth, and detect their movements. However, such two-dimensional (2D) image-based methods raise privacy concerns and fail when features of the face are hidden due to a mask, or if the face is turned sideways.
The solution may lie in optimizing facial detection using point cloud data (data obtained from a discrete set of data points) and a depth sensor. In fact, some previous studies have employed an estimation model based on the deep learning of 3D point cloud data in five face directions: frontal, diagonal frontal, right, left, and horizontal.
