Reliable Real-Time Optical Flow Estimation for Surveillance Applications

We present a reliable real-time optical flow estimation framework which can be used in surveillance applications and video analysis. In normal imaging environments, reliability can be achieved by combining an extended optical flow constraint with a smoothing procedure and a masking procedure. In noisy environments, total least squares is adopted to ensure accuracy. The proposed system is able to recover up to 31 frames of dense optical flow per second using a Xeon 3.06GHz workstation, which makes it very useful in a range of surveillance systems that are based on standard PC hardware.