Des techniques statistiques de détection d'objet ponctuel dans le ciel ou résolu dans la mer dans des images infrarouges de veille panoramique sont développées. Ces techniques sont adaptées aux inhomogénéités présentes dans ce type d'image. Elles ne sont fondées que sur l'analyse de l'information spatiale et ont pour objectif de maîtriser le taux de fausse alarme sur chaque image. Pour les zones de ciel, une technique conjointe de segmentation et détection adaptée aux variations spatiales de la luminosité moyenne est mise en œuvre et l'amélioration des performances auxquelles elle conduit est analysée. Pour les zones de mer, un détecteur de bord à taux de fausse alarme constant en présence d'inhomogénéités et de corrélations spatiales des niveaux de gris est développé et caractérisé. Dans chaque cas, la prise en compte des inhomogénéités dans les algorithmes statistiques s'avère essentielle pour maîtriser le taux de fausse alarme et améliorer les performances de détection. / Statistical detection techniques of point target in the sky or resolved target in the sea in infrared surveillance system images are developed. These techniques are adapted to inhomogeneities present in this kind of images. They are based on the spatial information analysis and allow the control of the false alarm rate in each image.For sky areas, a joint segmentation detection technique adapted to spatial variations of the mean luminosity is developed and its performance improvement is analyzed. For sea areas, an edge detector with constant false alarm rate when inhomogeneities and grey level spatial correlations are present is developed and characterized. In each case, taking into account the inhomogeneities in these statistical algorithms is essential to control the false alarm rate and to improve the detection performance.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / 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. / Vigilância se tornou, nos últimos anos, algo ubíquo em nossa sociedade. Cada dia que passa é mais notória a presença de sistemas inteligentes de vigilância em nosso dia-a-dia. Isso se deve tanto aos avanços tecnológicos alcançados nas últimas décadas (aumento da capacidade de processamento e armazenamento, miniaturização de dispositivos como detectores biométricos e câmeras de vídeo) como a constante sensação de insegurança vivida em vários países. Após os dias sombrios de 11/09, segurança e vigilância se tornaram algo primordial. Este trabalho visa o estudo de técnicas para o desenvolvimento de um sistema de vigilância para um estacionamento externo baseado em uma câmera estacionária. Tendo em vista que em um estacionamento externo é de suma importância que a vigilância seja feita tanto de dia quanto de noite, neste trabalho utilizamos uma câmera que captura imagens infravermelhas. Uma câmera infravermelha permite que enxerguemos objetos de interesse na cena até mesmo a noite. As imagens usadas nos experimentos realizados neste trabalho foram colhidas no campus da Universidade de Laval (Canadá) durante um estágio realizado no Canada Research Chair in Multipolar Infrared Vision. Um sistema de vigilância baseado em câmeras de vídeo geralmente possui três partes principais: (i) detecção de movimento, (ii) monitoramento e (iii) gerenciamento de eventos. Neste trabalho, utilizamos uma dinâmica técnica de subtração de plano de fundo para realizar a detecção de movimento (segmentação de movimento). Esta técnica se adapta às mudanças bruscas de iluminação na cena tornando o método de segmentação robusto a estas mudanças. Além disso, utilizamos análise de uxo de movimento para restringir a segmentação somente às regiões onde existem algum movimento na cena. A técnica de monitoramento de objetos em movimento usada neste trabalho é baseada em um ciclo de dois estágios: previsão e correção. Os eventos de interesse que ocorrem na área monitorada são modelados de forma explícita sendo então reconhecidos e interpretados. O foco principal deste trabalho é o reconhecimento de eventos suspeitos. Resultados experimentais obtidos mostram que tais técnicas são adequadas para um sistema de vigilância de um estacionamento externo baseado em uma câmera estacionária infravermelha. / Mestre em Ciência da Computação

Object tracking can be done in numerous ways, where the goal is to track a target through all frames in a sequence. The ground truth bounding box is used to initialize the object tracking algorithm. Object tracking can be carried out on infrared imagery suitable for military applications to execute tracking even without illumination. Objects, such as aircraft, can deploy countermeasures to impede tracking. The countermeasures most often mainly impact one wavelength band. Therefore, using two different wavelength bands for object tracking can counteract the impact of the countermeasures. The dataset was created from simulations. The countermeasures applied to the dataset are flares and Directional Infrared Countermeasures (DIRCMs). Different object tracking algorithms exist, and many are based on discriminative correlation filters (DCF). The thesis investigated the DCF-based trackers STRCF and ECO on the created dataset. The STRCF and the ECO trackers were analyzed using one and two wavelength bands. The following features were investigated for both trackers: grayscale, Histogram of Oriented Gradients (HOG), and pre-trained deep features. The results indicated that the STRCF and the ECO trackers using two wavelength bands instead of one improved performance on sequences with countermeasures. The use of HOG, deep features, or a combination of both improved the performance of the STRCF tracker using two wavelength bands. Likewise, the performance of the ECO tracker using two wavelength bands was improved by the use of deep features. However, the negative aspect of using two wavelength bands and introducing more features is that it resulted in a lower frame rate.

This thesis presented an overview of the development of a geolocating algorithm as part of a geoprocessor for raw satellite imagery. This algorithm was devised for and limited by the specifications of a state-of-the-art multispectral telescope designed by Aistech Space, hosted onboard the Guardian spacecraft, which will observe Earth through the visible, near infrared, and thermal infrared bands of the electromagnetic spectrum. The geolocation algorithm presented here is composed of the combination of two models. The first is a physical model, which makes use of spacecraft telemetry and external satellite-tracking data to approximate the geographical center of a sensed scene. Secondly, an optical model obtains a reference Landsat image based on the timestamp and approximated location of the sensed scene and utilizes image processing techniques to pinpoint a more precise geographical location of the sensed scene within acceptable limits. This performance was achieved in 77% of the cases considered. To conclude, a roadmap of the subsequent development topics and their relevance was laid out. / Detta examensarbete presenterar en översikt för utvecklingen av en geolokaliseringsalgoritm som en del av en geoprocessor för obearbetade satellitbilder. Algoritmen anpassades för och begränsades av specifikationerna för ett toppmodernt multispektralt teleskop designat av Aistech Space. Teleskopet kommer att finnas ombord på rymdfarkosten Guardian, där den är avsedd att observera jorden i de synliga, nära infraröda och termiska infraröda delarna av det elektromagnetiska spektrumet. Geolokaliseringsalgoritmen som presenteras i detta arbete är sammansatt av en kombination av två modeller. Den första är en fysisk modell, vilken använder sig av rymdfarkostens telemetri och extern satellitspårningsdata för att approximera det geografiska centrumet av en plats. Den andra är en optisk modell, vilken använder sig av en Landsat-referensbild baserad på tidsstämpeln och den ungefärliga positionen av platsen och använder sedan bildbehandlingstekniker för att fastställa en mer exakt geografisk position av platsen inom acceptabla gränser. Denna prestation lyckades uppnås i 77% av de övervägda fallen. Avslutningsvis lades en plan ut för de efterföljande utvecklingsämnena och deras relevans.