Statistical Modeling and Performance Characterization of a Real-Time Dual Camera Surveillance System

The engineering of computer vision systems that meet application speci c computational and accuracy requirements is crucial to the deployment of real-life computer vision systems. This paper illustrates how past work on a systematic engineering methodology for vision systems performance characterization can be used to develop a real-time people detection and zooming system to meet given application requirements. We illustrate that by judiciously choosing the system modules and performing a careful analysis of the in uence of various tuning parameters on the system it is possible to: perform proper statistical inference, automatically set control parameters and quantify limits of a dual-camera real-time video surveillance system. The goal of the system is to continuously provide a high resolution zoomed-in image of a persons head at any location of the monitored area. An omni-directional camera video is processed to detect people and to precisely control a high resolution foveal camera...

• Type: Conference
• Year: 2000
• Where: CVPR
• Authors: Michael Greiffenhagen, Visvanathan Ramesh, Dorin Comaniciu, Heinrich Niemann
• Keywords: Computer Vision, CVPR 2000, Omni-directional Camera Video, Resolution Foveal Camera, Tilt Parameters, Various Tuning Parameters, Vision Systems