Stable Multi-Target Tracking in Real-Time Surveillance Video

The majority of existing pedestrian trackers concentrate on maintaining the identities of targets, however systems for remote biometric analysis or activity recognition in surveillance video often require stable bounding-boxes around pedestrians rather than approximate locations. We present a multi-target tracking system that is designed specifically for the provision of stable and accurate head location estimates. By performing data association over a sliding window of frames, we are able to correct many data association errors and fill in gaps where observations are missed. The approach is multi-threaded and combines asynchronous HOG detections with simultaneous KLT tracking and Markov-Chain Monte-Carlo Data Association (MCMCDA) to provide guaranteed real-time tracking in high definition video. Where previous approaches have used ad-hoc models for data association, we use a more principled approach based on a Minimal Description Length (MDL) objective which accurately models the affi...

• Type: Conference
• Year: 2011
• Where: CVPR
• Authors: Ben Benfold and Ian Reid
• Keywords: 2011, Active Vision, Benfold, CCTV, Computer Vision, Cvpr, Oxford, Real Time Tracking, Reid, Research