Donald Wagner Hamilton

Intelligent Video for Protecting Crowded Sports Venues

Intelligent video in urban settings can be challenging due the presence of crowds, clutter, poor camera placement and continuously changing light conditions. The surveillance of sports venues is particularly difficult, because thousands of people can enter or exit a venue in short periods of time. This paper presents a case study of successfully monitoring a sports venue using a multi-camera multi-target tracking system. The system performed site-wide tracking throughout a network of calibrated cameras and was able to accurately track thousands of people in real-time under challenging conditions. The extracted tracking information was used to detect a range of real-time events such as crowd formation, left luggage, and loitering. In addition all video,track and event information was indexed and stored to allow operators to perform playback and forensic search. This paper will present an overview of the deployed system and discuss the challenges that were encountered during the deployment.

Image bias correction in structured light sensor

Structured light techniques have been used in a lot of applications. As a two-dimensional optical measurement method, structured light sensors are faster than one-dimensional point triangulation sensor while easier to calibrate and move than full-field three-dimensional sensors. The accuracy of structured light sensors mainly depends on the accuracy of both calibration and beam center extraction. In some applications with complicated surface shapes, the extracted center may not be the actual “true” center, which results in image bias. This paper presents a method to compensate the image bias and improve the measurement accuracy of structured light sensors. The basic concepts of image bias correction are given and some initial results are provided.

Video Analytics for Force Protection

For troop and military installation protection, modern computer vision methods must be harnessed to enable a comprehensive approach to contextual awareness. In this chapter we present a collection of intelligent video technologies currently under development at the General Electric Global Research Center, which can be applied to this challenging problem. These technologies include: aerial analysis for object detection and tracking, site-wide tracking from networks of fixed video cameras, person detection from moving platforms, biometrics at a distance and facial analysis for the purposes of inferring intent. We hypothesize that a robust approach to troop protection will require the synthesis of all of these technologies into a comprehensive system of systems.