1,993 research outputs found

    Applications of Factorization Theorem and Ontologies for Activity ModelingRecognition and Anomaly Detection

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    In this thesis two approaches for activity modeling and suspicious activity detection are examined. First is application of factorization theorem extension for deformable models in two dierent contexts. First is human activity detection from joint position information, and second is suspicious activity detection for tarmac security. It is shown that the first basis vector from factorization theorem is good enough to dierentiate activities for human data and to distinguish suspicious activities for tarmac security data. Second approach dierentiates individual components of those activities using semantic methodol- ogy. Although currently mainly used for improving search and information retrieval, we show that ontologies are applicable to video surveillance. We evaluate the domain ontologies from Challenge Project on Video Event Taxonomy sponsored by ARDA from the perspective of general ontology design principles. We also focused on the eect of the domain on the granularity of the ontology for suspicious activity detection

    Smart video sensors for 3D scene reconstruction of large infrastructures

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    The final publication is available at Springer via http://dx.doi.org/10.1007/s11042-012-1184-zThis paper introduces a new 3D-based surveillance solution for large infrastructures. Our proposal is based on an accurate 3D reconstruction using the rich information obtained from a network of intelligent video-processing nodes. In this manner, if the scenario to cover is modeled in 3D with high precision, it will be possible to locate the detected objects in the virtual representation. Moreover, as an improvement over previous 2D solutions, having the possibility of modifying the view point enables the application to choose the perspective that better suits the current state of the scenario. In this sense, the contextualization of the events detected in a 3D environment can offer a much better understanding of what is happening in the real world and where it is exactly happening. Details of the video processing nodes are given, as well as of the 3D reconstruction tasks performed afterwards. The possibilities of such a system are described and the performance obtained is analyzed.This work has been partially supported by the ViCoMo project (ITEA2 project IP08009 funded by the Spanish MICINN with project TSI-020400-2011-57), the Spanish Government (TIN2009-14103-C03-03, DPI2008-06737-C02-01/02 and DPI 2011-28507-C02-02) and European FEDER funds.Ripollés Mateu, ÓE.; Simó Ten, JE.; Benet Gilabert, G.; Vivó Hernando, RA. (2014). Smart video sensors for 3D scene reconstruction of large infrastructures. Multimedia Tools and Applications. 73(2):977-993. https://doi.org/10.1007/s11042-012-1184-zS977993732Atienza-Vanacloig V, Rosell-Ortega J, Andreu-Garcia G, Valiente-Gonzalez J (2008) People and luggage recognition in airport surveillance under real-time constraints. In: 19th international conference on pattern recognition, pp 1–4Cal3D (2011) http://gna.org/projects/cal3d/ . Accessed 19 July 2012Chang F, Chen CJ (2003) A component-labeling algorithm using contour tracing technique. In: 7th int. conference on document analysis and recognition, pp 741–745Cruz-Neira C, Sandin DJ, DeFanti TA, Kenyon RV, Hart JC (1992) The cave: audio visual experience automatic virtual environment. Commun ACM 35:64–72Fleck S, Busch F, Biber P, Strasser W (2006) 3D surveillance a distributed network of smart cameras for real-time tracking and its visualization in 3D. In: Conference on computer vision and pattern recognition workshop (CVPRW06), p 118Hoiem D, Efros AA, Hebert M (2005) Automatic photo pop-up. ACM Trans Graph 24:577–584Javed O, Shah M (2008) Automated multi-camera surveillance: algorithms and practice. Springer, New YorkLipton A, Fujiyoshi H, Patil R (1998) Moving target classification and tracking from real-time video. In: Proceedings of IEEE workshop on applications of computer vision, vol 1, pp 8–14Lloyd DH (1968) A concept of improvement of learning response in the taught lesson. In: Visual education, pp 23–25Osfield R, Burns D (2011) OpenSceneGraph. http://www.openscenegraph.org . Accessed 19 July 2012Rieffel EG, Girgensohn A, Kimber D, Chen T, Liu Q (2007) Geometric tools for multicamera surveillance systems. In: IEEE int. conf. on distributed smart camerasSebe I, Hu J, You S, Neumann U (2003) 3D video surveillance with augmented virtual environments. In: ACM SIGMM workshop on video surveillance, pp 107–112SENSE Consortium (2006) Smart embedded network of sensing entities. Web page: http://www.sense-ist.org (European Commission: IST Project 033279). Accessed 19 July 2012Sánchez J, Benet G, Simó JE (2012) Video sensor architecture for surveillance applications. Sensors 12(2):1509–1528Vouzounaras G, Daras P, Strintzis M (2011) Automatic generation of 3D outdoor and indoor building scenes from a single image. Multimedia Tools Appl. doi: 10.1007/s11042-011-0823-0Yan W, Kieran D, Rafatirad S, Jain R (2011) A comprehensive study of visual event computing. Multimedia Tools Appl 55:443–481Zúñiga M, Brémond F, Thonnat M (2006) Fast and reliable object classification in video based on a 3D generic model. In: Proceedings of the international conference on visual information engineering (VIE2006), pp 26–2

    Study of segmentation and identification techniques applied to environments with natural illumination and moving objects

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    La presente tesis está enmarcada en el área de visión por computador y en ella se realizan aportaciones encaminados a resolver el problema de segmentar automáticamente objetos en imágenes de escenas adquiridas en entornos donde se está realizando actividad, es decir, aparece movimiento de los elementos que la componen, y con iluminación variable o no controlada. Para llevar a cabo los desarrollos y poder evaluar prestaciones se ha abordado la resolución de dos problemas distintos desde el punto de vista de requerimientos y condiciones de entorno. En primer lugar se aborda el problema de segmentar e identificar, los códigos de los contenedores de camiones con imágenes tomadas en la entrada de un puerto comercial que se encuentra ubicada a la intemperie. En este caso se trata de proponer técnicas de segmentación que permitan extraer objetos concretos, en nuestro caso caracteres en contenedores, procesando imágenes individuales. No sólo supone un reto el trabajar con iluminación natural, sino además el trabajar con elementos deteriorados, con contrastes muy diferentes, etc. Dentro de este contexto, en la tesis se evalúan técnicas presentes en la literatura como LAT, Watershed, algoritmo de Otsu, variación local o umbralizado para segmentar imágenes en niveles de gris. A partir de este estudio, se propone una solución que combina varias de las técnicas anteriores, en un intento de abordar con éxito la extracción de caracteres de contenedores en todas las situaciones ambientales de movimiento e iluminación. El conocimiento a priori del tipo de objetos a segmentar nos permitió diseñar filtros con capacidad discriminante entre el ruido y los caracteres. El sistema propuesto tiene el valor añadido de que no necesita el ajuste de parámetros, por parte del usuario, para adaptarse a las variaciones de iluminación ambientales y consigue un nivel alto en la segmentación e identificación de caracteres.Rosell Ortega, JA. (2011). Study of segmentation and identification techniques applied to environments with natural illumination and moving objects [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10863Palanci

    A holistic review of cybersecurity and reliability perspectives in smart airports

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    Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence of smart airports. Services and systems powered by the IoT enable smart airports to have enhanced robustness, efficiency and control, governed by real-time monitoring and analytics. Smart sensors control the environmental conditions inside the airport, automate passenger-related actions and support airport security. However, these augmentations and automation introduce security threats to network systems of smart airports. Cyber-attackers demonstrated the susceptibility of IoT systems and networks to Advanced Persistent Threats (APT), due to hardware constraints, software flaws or IoT misconfigurations. With the increasing complexity of attacks, it is imperative to safeguard IoT networks of smart airports and ensure reliability of services, as cyber-attacks can have tremendous consequences such as disrupting networks, cancelling travel, or stealing sensitive information. There is a need to adopt and develop new Artificial Intelligence (AI)-enabled cyber-defence techniques for smart airports, which will address the challenges brought about by the incorporation of IoT systems to the airport business processes, and the constantly evolving nature of contemporary cyber-attacks. In this study, we present a holistic review of existing smart airport applications and services enabled by IoT sensors and systems. Additionally, we investigate several types of cyber defence tools including AI and data mining techniques, and analyse their strengths and weaknesses in the context of smart airports. Furthermore, we provide a classification of smart airport sub-systems based on their purpose and criticality and address cyber threats that can affect the security of smart airport\u27s networks

    Selective Screening of Rail Passengers, MTI 06-07

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    The threat of another major terrorist attack in the United States remains high, with the greatest danger coming from local extremists inspired by events in the Middle East. Although the United States removed the Taliban government and destroyed al Qaeda’s training camps in Afghanistan, events in Europe and elsewhere have shown that the terrorist network leadership remains determined to carry out further attacks and is capable of doing so. Therefore, the United States must systematically conduct research on terrorist strikes against transportation targets to distill lessons learned and determine the best practices for deterrence, response, and recovery. Those best practices must be taught to transportation and security professionals to provide secure surface transportation for the nation. Studying recent incidents in Europe and Asia, along with other research, will help leaders in the United States learn valuable lessons—from preventing attacks, to response and recovery, to addressing the psychological impacts of attacks to business continuity. Timely distillations of the lessons learned and best practices developed in other countries, once distributed to law enforcement, first responders, and rail- and subway-operating transit agencies, could result in the saving of American lives. This monograph focuses on the terrorist risks confronting public transportation in the United States—especially urban mass transit—and explores how different forms of passenger screening, and in particular, selective screening, can best be implemented to reduce those risks

    A fast airplane boarding strategy using online seat assignment based on passenger classification

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    The minimization of the turnaround time, the duration which an aircraft must remain parked at the gate, is an important goal of airlines to increase their profitability. This work introduces a procedure to minimize of the turnaround time by speeding up the boarding time in passenger aircrafts. This is realized by allocating the seat numbers adaptively to passengers when they pass the boarding gate and not before. Using optical sensors, an agility measure is assigned to each person and also a measure to characterize the size of her/his hand-luggage. Based on these two values per passenger and taking into account additional constraints, like reserved seats and the belonging to a group, a novel seat allocation algorithm is introduced to minimize the boarding time. Extensive simulations show that a mean reduction of the boarding time with approximately 15% is achieved compared to existing boarding strategies. The costs of introducing the proposed procedure are negligible, while the savings of reducing the turnaround time are enormous, considering that the costs generated by inactive planes on an airport are estimated to be about 30 $ per minute

    Enhancing airplane boarding procedure using vision based passenger classification

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    This paper presents the implementation of a new boarding strategy that exploits passenger and hand-luggage detection and classification to reduce the boarding time onto an airplane. A vision system has the main purpose of providing passengers data, in terms of agility coefficient and hand-luggage size to a seat assignment algorithm. The software is able to dynamically generate the passenger seat that reduces the overall boarding time while taking into account the current airplane boarding state. The motivation behind this work is to speed up of the passenger boarding using the proposed online procedure of seat assignment based on passenger and luggage classification. This method results in an enhancement of the boarding phase, in terms of both time and passenger experience. The main goal of this work is to demonstrate the usability of the proposed system in real conditions proving its performances in terms of reliability. Using a simple hardware and software setup, we performed several experiments recreating a gate entrance mock up and comparing the measurements with ground truth data to assess the reliability of the system

    Regulating privatized infrastructures and airport services

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    For a World Bank Institute course on transport privatization, the authors cover basic issues associated with the regulation of privatized airport infrastructure and services: 1) Economic characteristics of airport. Three types of activities are carried out in airports: essential operational services (aeronautical and non-aeronautical), handling services (aeronautical and non-aeronautical), and commercial activities. Demand for basic airport services is directly influenced by trip purpose. The two types of airline customers (business and leisure travelers) need different levels of flexibility and tend to travel at different times. Analyzing airport capacity (practical and saturation) under peak demand is essential to airport success. Among other important issues: runway cost, level and volume of service, pollution, congestion, and air traffic control. 2) Recent trends in the airport industry. The movement toward privatization may involve public ownership and private operation, including joint ventures; partial or majority divestiture; management contracts; and BOT (build-operate-transfer) schemes and variants, including BOOT (build-own-operate-transfer) schemes and LDO (lease-develop-operate) schemes. Or it may involve private ownership and operation. 3) Price regulation. Topics covered include traditional pricing policies'price regulation through an RPI-X formula; charges for congestion, noise, and other externalities; investment plans; and design of the regulatory system. 4) Regulation of quality in the industry. Topics covered: regulation of services to passengers (as measured by targets for check-in queues, immigration queues, baggage reclaim queues, concourse crowding, shopping, parking, and so on); fault repair times; average levels of passenger boarding and disembarkation and baggage delivery; safety; and investment obligation. 5) Performance indicators in the industry. Topics covered: strategic indicators and other financial indicators (including revenues), as well as indicators of cost, productivity, and quality of service.Transport and Trade Logistics,Public Sector Economics&Finance,Banks&Banking Reform,Environmental Economics&Policies,Decentralization,Roads&Highways,Airports and Air Services,Public Sector Economics&Finance,Banks&Banking Reform,Transport and Trade Logistics

    A holistic review of cybersecurity and reliability perspectives in smart airports

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    Advances in the Internet of Things (IoT) and aviation sector have resulted in the emergence of smart airports. Services and systems powered by the IoT enable smart airports to have enhanced robustness, efficiency and control, governed by real-time monitoring and analytics. Smart sensors control the environmental conditions inside the airport, automate passenger-related actions and support airport security. However, these augmentations and automation introduce security threats to network systems of smart airports. Cyber-attackers demonstrated the susceptibility of IoT systems and networks to Advanced Persistent Threats (APT), due to hardware constraints, software flaws or IoT misconfigurations. With the increasing complexity of attacks, it is imperative to safeguard IoT networks of smart airports and ensure reliability of services, as cyber-attacks can have tremendous consequences such as disrupting networks, cancelling travel, or stealing sensitive information. There is a need to adopt and develop new Artificial Intelligence (AI)-enabled cyber-defence techniques for smart airports, which will address the challenges brought about by the incorporation of IoT systems to the airport business processes, and the constantly evolving nature of contemporary cyber-attacks. In this study, we present a holistic review of existing smart airport applications and services enabled by IoT sensors and systems. Additionally, we investigate several types of cyber defence tools including AI and data mining techniques, and analyse their strengths and weaknesses in the context of smart airports. Furthermore, we provide a classification of smart airport sub-systems based on their purpose and criticality and address cyber threats that can affect the security of smart airport\u27s networks
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