Change Detection and Tracking Using Pyramid Transform Techniques

An automated, or "smart", surveillance system must be sensitive to small object motion wherever it may occur within a large field of view. The system must also be capable of distinguishing changes of interest from other image activity or noise. Yet the data processing capabilities of practical systems is often quite limited. To achieve these performance objectives at a low data rate, a pyramid based image preprocessor has been constructed that can compute frequency tuned "change energy" measures in real time. A microprocessor then examines a relatively small set of these measures and follows a foveal search strategy to isolate moving objects for tracking or for more detailed analysis.