ID Management Strategies for Interactive Systems in Multi-Camera Scenarios

This paper presents a novel approach towards identity management strategies for application in large scale interactive systems while separating pure detection from the identity management processes. Detection is achieved by employing a scalable, modal, network-based, real-time multi-camera tracking system in which numerous cameras are used to cover large areas. Objects are detected by employing blob detection and image pre-processing algorithms. The proposed identity handling algorithm covers standard tracking as well as solving Split, Merge, and Handover problems between adjacent cameras. General ID handling strategies are introduced which allow reliable tracking and simple access to high-level movement data for later movement analysis. Results in terms of accuracy and technical feasibility are given, gathered from a pilot installation at a public event.