Moving Object Detection and Tracking for Video Surveillance: A Review

This paper presents a review and systematic study on the moving object detection and surveillance of the video as it is an important and challenging task in many computer vision applications, such as human detection, vehicles detection, threat, and security. Video surveillance is a dynamic environment, especially for human and vehicles and for specific object in case of security is one of the current challenging research topics in computer vision. It is a key technology to fight against terrorism, crime, public safety and for efficient management of accidents and crime scene going on now days. The paper also presents the concept of real time implementation computing task in video surveillances system. In this review paper various methods are discussed were evaluation of order to access how well they can detect moving object in an outdoor/indoor section in real time situation

Post-processing approaches for improving people detection performance

This is the author’s version of a work that was accepted for publication in Computer Vision and Image Understanding. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Vision and Image Understanding, 133 (2015) DOI: 10.1016/j.cviu.2014.09.010People detection in video surveillance environments is a task that has been generating great interest. There are many approaches trying to solve the problem either in controlled scenarios or in very specific surveillance applications. We address one of the main problems of people detection in video sequences: every people detector from the state of the art must maintain a balance between the number of false detections and the number of missing pedestrians. This compromise limits the global detection results. In order to reduce or relax this limitation and improve the detection results, we evaluate two different post-processing subtasks. Firstly, we propose the use of people-background segmentation as a filtering stage in people detection. Then, we evaluate the combination of different detection approaches in order to add robustness to the detection and therefore improve the detection results. And, finally, we evaluate the successive application of both post-processing approaches. Experiments have been performed on two extensive datasets and using different people detectors from the state of the art: the results show the benefits achieved using the proposed post-processing techniques.This work has been partially supported by the Spanish Government (TEC2011-25995 EventVideo)

Monitoring of railroad crossing using digital image

Embora a massificação e a utilização de comboios tenha contribuído para um maior bem-estar por parte das populações, existem problemas inerentes, sendo um deles os acidentes e as consequências dos mesmos que ocorrem nas passagens de nível. Esta dissertação surge com o propósito de investigar e testar uma solução que diminua e evite este tipo de situações. Tendo em conta o maior poder computacional existente nos dias de hoje e a área de visão por computador, juntamente com os avanços nas comunicações em rede, que cada vez mais possibilita o aparecimento de soluções para monitorização de espaços em tempo real, consideramos que esta pode ser uma solução e esta dissertação dá suporte a essa escolha. A solução tem como base um sistema de vídeo instalado na passagem de nível e a análise do mesmo, detetando possíveis obstáculos e enviando um aviso para os comboios nas proximidades. Foram estudadas várias possibilidades e soluções, entre elas algumas frameworks e algoritmos utilizados na deteção e classificação de objetos. O nível de sucesso do trabalho realizado é avaliado com base nos resultados apresentados, quer a nível de taxas de acerto como a nível de desempenho do sistema.Although the massification and use of trains has contributed to a increased well-being of the population, there are inherent problems, one of which are the accidents and their consequences that occur at level crossings. This dissertation arises with the purpose of investigating and testing a monitoring solution that could help reducing or avoid this type of situations. Taking into account the greater computational power that exists today and the area of computer vision, together with the new advances in the network communication, which increasingly allows the appearance of solutions for real-time space monitoring, we consider this can be a solution and this thesis gives support to this choice. The tested solution is based on a computer video system with a digital camera installed on the level crossing and an offline analysis of the acquired images, detecting possible obstacles that could eventually generate a warning to be sent to nearby trains. Several possibilities and solutions were studied, among them some frameworks and algorithms used in the detection and classification of objects. The level of success of the developed project is evaluated based on the presented results, both in terms of hit rates and system performance.Mestrado em Engenharia de Computadores e Telemátic