The OBSERVER: an intelligent and automated video surveillance system

• Main Author: Duque, Duarte
• Publication Date: 2006
• Other Authors: Santos, Henrique Dinis dos, Cortez, Paulo
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: https://hdl.handle.net/1822/5602
• topic: Motion detection; Image segmentation; Tracking; Behaviour analysis; moving object detection; behavior detection; Science & Technology

In this work we present a new approach to learn, detect and predict unusual and abnormal behaviors of people, groups and vehicles in real-time. The proposed OBSERVER video surveillance system acquires images from a stationary color video camera and applies state-of-the-art algorithms to segment and track moving objects. The segmentation is based in a background subtraction algorithm with cast shadows, highlights and ghost’s detection and removal. To robustly track objects in the scene, a technique based on appearance models was used. The OBSERVER is capable of identifying three types of behaviors (normal, unusual and abnormal actions). This achievement was possible due to the novel N-ary tree classifier, which was successfully tested on synthetic data.