Adaptive multisensor change detection

This paper describes an approach for intruder detection by a remote surveillance system. Emphasis is placed on the development of multispectral vision techniques for the extraction of information from a noisy and cluttered environment. This approach uses adaptive detection for operation under changing illumination and thermal environments. The system is initialized with an operator-guided segmentation to partition the scene into regions of similar noise characteristics and processing priorities. Images from a color TV and a FLIR are registered electronically and a common segmentation is used for both. Detection processing in corresponding regions of the two sensors' images are closely coupled. A system testbed is described and several processing sequences are presented which illustrate the approach.