Tracking gaze direction from far-field surveillance cameras

Abstract

We present a real-time approach to estimating the gaze direction of multiple individuals using a network of far-field surveillance cameras. This work is part of a larger surveillance system that utilizes a network of fixed cameras as well as PTZ cameras to perform site-wide tracking of individuals. Based on the tracking information, one or more PTZ cameras are cooperatively controlled to obtain close-up facial images of individuals. Within these close-up shots, face detection and head pose estimation are performed and the results are provided back to the tracking system to track the individual gazes. A new cost metric based on location and gaze orientation is proposed to robustly associate head observations with tracker states. The tracking system can thus leverage the newly obtained gaze information for two purposes: (i) improve the localization of individuals in crowded settings, and (ii) aid high-level surveillance tasks such as understanding gesturing, interactions between individuals, and finding the object-of-interest that people are looking at. In security application, our system can detect if a subject is looking at the security cameras or guard posts.