Advanced image-processing tools for counting people in tourist site-monitoring applications

This work aims at demonstrating the usefulness of exploiting novel image-pr ocessing tools for moving-object detection and classification in the contex t of an actual application involving the remote monitoring of a tourist sit e. The application concerns outdoor people counting for tourist-how estimat ion in a constrained environment. The technical problems to be solved are c oncerned with: (a) the design and implementation of low-complexity backgrou nd updating and change detection algorithms able to adapt themselves to the time-varying illumination scene conditions, and (b) the integration of rea l-time pattern-recognition tools in order to distinguish group of persons t o be counted from other objects present in the scene. The achieved results have proven that the proposed system makes it possible to obtain reliable p eople counting in different environmental situations, with an absolute mean error at most equal to 10%. (C) 2001 Elsevier Science B.V. All rights rese rved.