Smartphone Inertial Sensors and CCTV Facial Dataset for Human identification

This multimodal biometric dataset combines smartphone inertial gait signals with facial recordings for human identification research. Contains data from 400 participants (39% female, 61% male, ages 18-49) performing 10 walking trials each at Koya University, Kurdistan Region, Iraq. Dataset includes 4,000 inertial sensor recordings (accelerometer, gyroscope, magnetometer at 30 Hz) capturing distinctive gait signatures with high consistency across trials. Additionally provides 20,000 facial image frames from 100 selected participants using dual-camera CCTV setup: frontal and side views with minimal motion blur.Synchronized inertial-visual data enables multimodal fusion experiments and temporal alignment studies. Collection methodology ensures realistic real-world conditions with natural smartphone holding positions, making this dataset valuable for practical biometric system development.