Reconhecimento de atividades suspeitas em ambiente externo via análise de vídeo infravermelho

• Ano de defesa: 2011
• Autor(a) principal: Fernandes, Henrique Coelho
• Orientador(a): Barcelos, Célia Aparecida Zorzo
• Banca de defesa: Travençolo, Bruno Augusto Nassif , Medeiros, Fátima Nelsizeuma Sombra de, Batista, Marcos Aurélio
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Uberlândia
• Programa de Pós-Graduação: Programa de Pós-graduação em Ciência da Computação
• Departamento: Ciências Exatas e da Terra
• País: BR
• Palavras-chave em Português: Sistema automático de vigilância; Reconhecimento de eventos suspeitos; Vídeos infravermelhos; Segmentação de plano de fundo; Computação; Banco de dados
• Palavras-chave em Inglês: Automatic surveillance system; Suspicious event recognition; Infrared imagery; Background subtraction
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufu.br/handle/123456789/12518

Surveillance has become, in the last years, something ubiquity in our society. Every day it is more notorious the presence of intelligent systems for surveillance in our everyday life. This is due to technological advances achieved in recent decades (storage and processing speed increasing, miniaturization of devices like biometric detectors and video cameras) as the constant feeling of insecurity experienced in several countries. Following the dark days of 9/11, security and surveillance became paramount. This work aims the study of techniques for the development of a surveillance system of an outdoor parking lot based on a stationary camera. Considering that in an outdoor parking lot it is very important that the surveillance is made both day and night, in this work we use an infrared camera to record images. An infrared camera allows to see objects of interest in the scene even at night. The images used for the experiments in this work were recorded by the student in Laval University campus (Canada) during an internship he held in the "Canada Research Chair in Multipolar Infrared Vision". A surveillance system based on video cameras is usually composed of three parts: (i) motion detection, (ii) tracking and (iii)event management. In this work, we use a dynamic background subtraction technique to detect motion (motion segmentation). This technique adapts to abrupt changes on the scene's illumination making the technique robust to this changes. Besides, we use ow analysis to restrict the segmentation process only to regions where we have motion in the scene. The object tracking technique used is based on a two phase cycle: prediction and correction. The events of interest which occur in the monitored area are modeled explicitly and then recognized and interpreted. The main goal of this project is to recognize suspicious events. Experimental results show that such techniques are suitable for a surveillance system for an outdoor parking lot based on a infrared stationary camera.