Video surveillance is an active research area in Computer Vision and Machine Learning. It received a lot of attention in the last few decades. Maritime surveillance is the act of effective detection/recognition of all maritime activities that have impact on economy, security or the environment. The maritime environment is a dynamic environment. Factors such as constant moving of waves, sun reflection over the sea surface, rapid change in lightning due to the sun reflection over the water surface, movement of clouds and presence of moving objects such as airplanes or birds, makes the maritime environment very challenging. In this work, we propose a method for detecting a motion generated by a maritime vehicle and then identifying the type of this vehicle using classification methods. A new maritime video database was created and tested. Classifying the type of vehicles have been tested by comparing 13 image features, and two SVM solving algorithms. In motion detection part, multiple smoothing filters were tested in order to minimize the false positive rate generated by the water surface movement, the results have been compared to optical flow, a well known method for motion detection. / Master of Science

L’essor des transports à une échelle globale s’inscrit dans un phénomène de mondialisation et 90% des biens échangés au travers le monde sont effectués par voie maritime. La maritimisation se définit comme un processus de dépendance économique des états au trafic maritime due à ce phénomène de mondialisation (Vigarié 1983). Ce phénomène transforme les territoires, et principalement les espaces côtiers mais a également comme conséquence une territorialisation des espaces maritimes, à savoir une utilisation et gestion des espaces pour les activités humaines. L'utilisation de cet espace a augmenté depuis 1970 et principalement le transport, que ce soit via porte-conteneurs ou tanker (Rodrigue, Comtois, and Slack 2013). Cela forme ainsi un réseau de transport maritime et d’approvisionnement lié à l’emplacement des ports dans le monde et des routes maritimes les reliant. Cependant ce réseau s’étend sur un espace vaste et dynamique, l’espace maritime, qui peut générer des risques pour l’usage de l’espace à des fins de transports.Ce réseau d’approvisionnement est vulnérable face à certains événements (perturbations) pouvant affecter la performance du réseau d’approvisionnement (Achurra-Gonzalez et al. 2016) : les tempêtes, les pénuries, la piraterie maritime, les fermetures de canaux sont des événements ayant une influence sur l’efficacité d’un réseau d’approvisionnement. Cette vulnérabilité est liée à plusieurs facteurs (Wagner and Neshat 2010) : les variations de l’offre et de la demande, les risques économiques, et à la structure du réseau et de l’espace maritime, les risques géographiques. L’ensemble de ces risques peuvent être mesurés et quantifiés dans les caractéristiques topologiques, géométriques et relationnelles des graphes. Un graphe est un ensemble de noeuds relié par un ensemble de lien. Les graphes sont utilisés pour la formalisation des réseaux, notamment des réseaux de transports (Ducruet and Lugo 2013).Afin de tester les perturbations sur les caractéristiques du réseau, un système de simulation est mis en place. Pour cela, les perturbations sont modélisées par des objets spatio-temporels ayant une influence sur l’accessibilité à l’espace des navires. Au travers d’un système multi-agents (Ferber 1997), ces navires prennent des décisions face aux perturbations (changement de route, de destination, report ou annulation du voyage). Ces comportements individuels, une fois agrégés, par la pondération des noeuds et des liens du graphe, permettent d’évaluer les variations topologiques et géométriques du graphe en fonction des perturbations dans l’espace maritime, grâce à des indicateurs utilisés pour mesurer la vulnérabilité des réseaux (Gleyze 2005). Ainsi cette recherche permet de mieux comprendre l’influence de ces perturbations sur le fonctionnement d’un réseau d’approvisionnement dans un espace maritime. / Transportation on a global scale is due to the globalization process. Today, 90% of goods in the world are traded by sea. Maritimization is defined as a process of increased economic dependence of states on maritime traffic (Vigarié 1983). This phenomenon transforms territories, mainly the coastal areas, but also results in a territorialization of maritime spaces, which means a use and a management of maritime space for human activities. The use of this space for transportation has increased since 1970, whether through container ships or tanker (Rodrigue, Comtois, and Slack 2013). These trips have created a network which linked the locations of the ports in the world by the sea routes of shipping. However, this network extends over a vast and dynamic space, maritime space, which can generate risks for the use of space for transportation.This supply network is vulnerable to certain events (disruptions) that may affect the performance of the supply network (Achurra-Gonzalez et al., 2016): storms, shortages or maritime piracy have an influence on the efficiency of a supply network. This vulnerability is linked to several factors (Wagner and Neshat 2010): variations in supply and demand, which are economical risks, and the structure of the network and maritime space, which are geographical risks. All these can be measured and quantified by the topological, geometric and relational properties of graphs. A graph is a set of nodes connected by a link set. The graphs are used for the formalization of networks, notably transport networks (Ducruet and Lugo 2013).To test the disruptions on the characteristics of the network, a simulation system is used. In the simulations, disruptions are modeled by space-time objects having an influence on the accessibility of the vessels. Through a multi-agent system (Ferber 1997), these ships make decisions about disruptions (change of route, destination, postponement or cancellation of the trip). These individual behaviors, once aggregated by the weighting of the nodes and links of the graph, allow evaluating the topological and geometric variations which represent the influence of disruptions on the martitime network. Theses variations can be measured by indicators of the vulnerability of network (Gleyze 2005). This research allows us to improve the understanding on the influence of these disruptions on a network within a dynamic space.

Human operators of modern surveillance systems are confronted with an increasing amount of trajectory data from moving objects, such as people, vehicles, vessels, and aircraft. A large majority of these trajectories reflect routine traffic and are uninteresting. Nevertheless, some objects are engaged in dangerous, illegal or otherwise interesting activities, which may manifest themselves as unusual and abnormal trajectories. These anomalous trajectories can be difficult to detect by human operators due to cognitive limitations. In this thesis, we study algorithms for the automated detection of anomalous trajectories in surveillance applications. The main results and contributions of the thesis are two-fold. Firstly, we propose and discuss a novel approach for anomaly detection, called conformal anomaly detection, which is based on conformal prediction (Vovk et al.). In particular, we propose two general algorithms for anomaly detection: the conformal anomaly detector (CAD) and the computationally more efficient inductive conformal anomaly detector (ICAD). A key property of conformal anomaly detection, in contrast to previous methods, is that it provides a well-founded approach for the tuning of the anomaly threshold that can be directly related to the expected or desired alarm rate. Secondly, we propose and analyse two parameter-light algorithms for unsupervised online learning and sequential detection of anomalous trajectories based on CAD and ICAD: the sequential Hausdorff nearest neighbours conformal anomaly detector (SHNN-CAD) and the sequential sub-trajectory local outlier inductive conformal anomaly detector (SSTLO-ICAD), which is more sensitive to local anomalous sub-trajectories. We implement the proposed algorithms and investigate their classification performance on a number of real and synthetic datasets from the video and maritime surveillance domains. The results show that SHNN-CAD achieves competitive classification performance with minimum parameter tuning on video trajectories. Moreover, we demonstrate that SSTLO-ICAD is able to accurately discriminate realistic anomalous vessel trajectories from normal background traffic.

Dans les années 1970, le trafic de stupéfiants a connu une rapide expansion, et n’a cessé, depuis, de s’accroître pour se mondialiser dans les années 1990 et atteindre une dimension géopolitique.De grands axes maritimes d’acheminement des différentes drogues exploités par les grandes organisations criminelles sont apparus, et il est devenu évident que les mesures qui permettent au secteur maritime de contribuer au développement des échanges mondiaux, et donc à la prospérité économique, l’ont rendu particulièrement propice au développement de ce type de trafic.Face à l’importance de la menace que constitue le transport maritime de stupéfiants, les Etats ont pris conscience de la nécessité d’en étendre et d’en rationaliser la répression à l’échelon international.Avec le temps, plusieurs conventions internationales, toujours en vigueur, ont vu le jour, sous l’égide des Nations Unies. La dernière en date, la Convention contre le trafic illicite de stupéfiants et des substances psychotropes, signée à Vienne en 1988, détermine, dans son article 17, le cadre de l’arraisonnement des navires suspecté de se livrer à un tel trafic en haute mer, mais, ce qui constitue le caractère propre d’une pareille capacité d’action est qu’elle doit s’inclure dans le respect des deux principes fondamentaux que sont, d’une part, la souveraineté des Etats, d’autre part, la liberté des mers définie par la Convention de Montego Bay de 1982, ceux-ci pouvant être antinomiques de celle-là. Avec la lutte contre le transport maritime de stupéfiants, la liberté des mers est devenue une liberté « encadrée ».Ceci pose de nombreuses difficultés d’interprétation et d’application des textes, qui ont conduit les Etats, par ailleurs souvent gênés dans leur action par la multiplication des structures intervenantes, à rechercher des solutions de coopération sur un plan opérationnel ou plus globalement avec des accords régionaux, pour résoudre de manière ponctuelle ou plus générale, certains types de problèmes.Dans ce contexte, les gouvernements ont en particulier perçu la nécessité de mettre en place des séries de mesures pratiques destinées à prévenir les menaces au niveau des différents maillons du réseau de transport maritime, singulièrement, et tout d’abord, en établissant un système d’information et de surveillance des approches maritimes, ensuite, en adoptant un ensemble de mesures de nature à organiser une meilleure sûreté portuaire avec le Code international pour la sûreté des navires et des ports (Code ISPS) et une meilleure sûreté concernant les conteneurs avec la Container security Initiative américaine.Là encore, l’instauration de cadres de coopération juridique et opérationnelle demeure, aujourd’hui comme pour le futur, une condition sine qua non du succès de la lutte contre un fléau mondial. / In the 1970s, the drug trafficking underwent a fast growth and continually increased to globalize in the 1990s reaching a geopolitical dimension.Criminal organizations began to use large sea routes to transport the flow of drugs. These increased sea routes along with the measures related to the maritime sector contributed to the development of the world exchanges and the economic prosperity. Thus, this turned to be convenient to the development of drug trafficking.This important threat of sea transportation of narcotics made the States aware that it was necessary to repress this threat at international level.The previous international Agreements that were established by the United Nations are still valid. The latest Convention against the illicit traffic in Narcotics Drugs and Psychotropic substances, signed in Vienna in 1988 under article 17 determines how ships suspected of engaging in drug trafficking in open sea would be inspected.The Montego Bay Agreement of 1982 defined the freedom of seas along with the States desire to remain sovereign are two basic fundamental principles combined in this capacity. However with the fight against the drug trafficking over the seas, the freedom of seas became framed.The numerous difficulties of interpretation and application of texts led States, often hampered in their action by many structures, to look for solutions for cooperation on an operational plan or more globally with regional agreements, to meet short or long term solutions.In this context, the governments mainly perceived the necessity of setting up a series of practical measures intended to prevent the threats at the level of the various links of the maritime transport network, first of all, by establishing an information and monitoring system of the maritime approaches, then, by adopting a set of measures likely to organize better harbour safety with the International Ship and Port Security Code (code ISPS) and better safety concerning containers with American security Container Initiative.Once again, the institution of frames of legal and operational cooperation remains, today as for the future, an indispensable condition of the success of the fight against a world plague.

Context. A large portion of all the transportation in the world consists of voyages over the sea. Systems such as Automatic Identification Systems (AIS) have been developed to aid in the surveillance of the maritime traffic, in order to help keeping the amount accidents and illegal activities down. In recent years a lot of time and effort has gone into automated surveillance of maritime traffic, with the purpose of finding and reporting behaviour deviating from what is considered normal. An issue with many of the present approaches is inaccuracy and the amount of false positives that follow from it. Objectives. This study continues the work presented by Woxberg and Grahn in 2015. In their work they used quadtrees to improve upon the existing tool STRAND, created by Osekowska et al. STRAND utilizes potential fields to build a model of normal behaviour from received AIS data, which can then be used to detect anomalies in the traffic. The goal of this study is to further improve the system by adding statistical analysis to reduce the number of false positives detected by Grahn and Woxberg's implementation. Method. The method for reducing false positives proposed in this thesis uses the charge in overlapping potential fields to approximate a normal distribution of the charge in the area. If a charge is too similar to that of the overlapping potential fields the detection is dismissed as a false positive. A series of experiments were ran to find out which of the methods proposed by the thesis are most suited for this application.   Results. The tested methods for estimating the normal distribution of a cell in the potential field, i.e. the unbiased formula for estimating the standard deviation and a version using Kalman filtering, both find as many of the confirmed anomalies as the base implementation, i.e. 9/12. Furthermore, both suggested methods reduce the amount of false positives by 11.5% in comparison to the base implementation, bringing the amount of false positives down to 17.7%. However, there are indications that the unbiased method has more promise. Conclusion. The two proposed methods both work as intended and both proposed methods perform equally. There are however indications that the unbiased method may be better despite the test results, but a new extended set of training data is needed to confirm or deny this. The two methods can only work if the examined overlapping potential fields are independent from each other, which means that the methods can not be applied to anomalies of the positional variety. Constructing a filter for these anomalies is left for future study.

Approved for public release; distribution in unlimited. / This study analyzes the effective use of multiple unmanned aerial vehicles (UAVs) for the Navy's Surface Search and Control mission. In the future, the Navy hopes to leverage the capabilities of a family of UAVs to provide increased situational awareness in the maritime environment. This family of UAVs includes a Broad Area Maritime Surveillance (BAMS) UAV and Vertical Take-Off UAVs (VTUAVs). The concepts of operations for how these UAVs work together have yet to be determined. Questions exist about the best number of UAVs, types of UAVs, and tactics that will provide increased capabilities. Through modeling and agent-based simulation, this study explores the validity of future UAV requirements and provides insights into the effectiveness of different UAV combinations. For the scenarios modeled, the best UAV combination is BAMS plus two or three VTUAVs. However, analysis shows that small numbers of VTUAVs can perform as well without BAMS as they do with BAMS. For combinations with multiple UAVs, BAMS proves to be a valuable asset that not only reduces the number of missed classifications, but greatly improves the amount of coverage on all contacts in the maritime environment. BAMS tactics have less effect than the mere presence of BAMS itself. / Lieutenant, United States Navy