Abstract

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed.

Highlights

  • IntroductionThe main aim of this project is to automate the supervision of commercial aircraft servicing operations on the ground at airports (in bounded areas known as aprons)

  • This paper describes work undertaken on the EU project AVITRACK

  • The servicing operations are monitored from multiple cameras that are mounted on the airport building surrounding the apron area, each servicing operation is a complex 30minute routine involving the interaction between aircraft, people, vehicles, and equipment

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Summary

Introduction

The main aim of this project is to automate the supervision of commercial aircraft servicing operations on the ground at airports (in bounded areas known as aprons). The output of this— the scene tracking module—is the predicted physical (i.e., real-world) objects in the monitored scene. These objects are subsequently passed (via a spatiotemporal coherency filter) to a scene understanding module where the activities within the scene are recognised. This result is fed— in real time—to apron managers at the airport. More details of the complete system are given in [2]

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