Study on Intelligent Facial Expressions of Humanoid Robot

This study describes the development of a motion control scheme for an artificial robot head that consists of four angles of freedom that lean against the neck and rotate freely laterally. This overview describes how vision helps to coordinate such behaviors, especially how the motor system uses sensory information to find the information needed for each behaviour. This work describes the creation of a human-like facial mechanism with simplified complexity to generate a human-like facial expression. A unique feature of this face robot is that it uses far fewer actuators. Only trio servomotors were used for facial movements, and five were used for the remaining head movements. In addition, the modular architecture allows you to achieve the required number of facial expressions in a single frame. Because the robot has an audio system and a camera in each eye, it uses auditory and visual sensitivities to identify, interact, and enhance the expressive process. From computer vision and computer graphics to multimedia processing, some application areas benefit from highlight detection because the detected highlights show the visual meaning of different sections of the visual stimulus. For 360-degree visual stimuli, photos and videos need to capture the entire scene in 3D space. Therefore, transferring an entire video or generating an entire scene can waste resources. In addition, if you can predict visually important areas in your image, you can process those areas in more detail.