Real-Time Head Orientation and Eye-Tracking Algorithm Using Adaptive Feature Extraction and Refinement Mechanisms - Ming-Chang Ye; Jian-Jiun Ding (Engineering Proceedings, 2025)
We propose a fast eye-tracking method that takes the depth image and the gray-scale infrared (IR) image using a traditional image processing algorithm. As an IR image contains one face and the corresponding depth image, the method locates the real coordinate of the camera with a high speed (>90 frames per second) and with and acceptable error. The method takes advantage of the depth information to quickly locate the face by shrinking the eyeballs. The method decreases the error rate but accelerates the operation speed. After finding the face region, less complicated computer vision algorithms are used at a high execution speed. Refinement mechanisms for extracting features and determining edge distribution are used to locate the eyeball’s position and transform the pixel coordinate of the image to the real coordinate.