Vision Lab

Face Detection

Face Detection in Complex Background Environment

This research deals with a human surveillance system with integrated face understanding technologies to recognize personal identities in real time. The focus is on developing automated visual identification of face image sequences automatically detected and tracked by a closed-loop mechanism using conventional surveillance cameras. The system performs face detection and tracking robustly in real-time under a wide range of lighting and scale variations by combining motion and facial appearance models. The faces in a scene are detected using a machine-learning algorithm and the detected faces are tracked all the time, which helps the detection on next frame. The surveillance system then performs real-time face recognition, which is invariant to large changes in lighting, facial expressions, and pose.

Video Demonstrations

Pose Variant Face Detection

Upper Body Tracking with Kalman Tracker