AttentionBase: A Facial Landmark-Based Dataset for Visual Attention and Drowsiness Monitoring

AttentionBase is a labeled dataset containing 14,127 samples collected from 200 participants during reading and browsing tasks. It includes facial landmark coordinates, Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), and timestamps, all captured at 20 FPS using MediaPipe, Dlib, and OpenCV. The data is stored in CSV (comma-separated values) format, making it easy to use with a wide range of machine learning and data analysis tools. This dataset is intended for research in visual attention monitoring, drowsiness detection, and human-computer interaction.