15,392 research outputs found

    Visual servoing of an autonomous helicopter in urban areas using feature tracking

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    We present the design and implementation of a vision-based feature tracking system for an autonomous helicopter. Visual sensing is used for estimating the position and velocity of features in the image plane (urban features like windows) in order to generate velocity references for the flight control. These visual-based references are then combined with GPS-positioning references to navigate towards these features and then track them. We present results from experimental flight trials, performed in two UAV systems and under different conditions that show the feasibility and robustness of our approach

    STV-based Video Feature Processing for Action Recognition

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    In comparison to still image-based processes, video features can provide rich and intuitive information about dynamic events occurred over a period of time, such as human actions, crowd behaviours, and other subject pattern changes. Although substantial progresses have been made in the last decade on image processing and seen its successful applications in face matching and object recognition, video-based event detection still remains one of the most difficult challenges in computer vision research due to its complex continuous or discrete input signals, arbitrary dynamic feature definitions, and the often ambiguous analytical methods. In this paper, a Spatio-Temporal Volume (STV) and region intersection (RI) based 3D shape-matching method has been proposed to facilitate the definition and recognition of human actions recorded in videos. The distinctive characteristics and the performance gain of the devised approach stemmed from a coefficient factor-boosted 3D region intersection and matching mechanism developed in this research. This paper also reported the investigation into techniques for efficient STV data filtering to reduce the amount of voxels (volumetric-pixels) that need to be processed in each operational cycle in the implemented system. The encouraging features and improvements on the operational performance registered in the experiments have been discussed at the end

    Developing Executable Digital Models with Model-Based Systems Engineering – An Unmanned Aerial Vehicle Surveillance Scenario Example

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    There is an increase in complexity in modern systems that causes inconsistencies in the iterative exchange loops of the system design process and in turn, demands greater quality of system organization and optimization techniques. A recent transition from document-centric systems engineering to Model-Based Systems Engineering (MBSE) is being documented in literature from various industries to address these issues. This study aims to investigate how MBSE can be used as a starting point in developing digital twins (DT). Specifically, the adoption of MBSE for realizing DT has been investigated, resulting in various literature reviews that indicate the most prevalent methodologies and tools used to enhance and validate existing and future systems. An MBSE-enabled template for virtual model development was executed for the creation of executable models, which can serve as a research testbed for DT and system and system-of-systems optimization. This study explores the feasibility of this MBSE-enabled template by creating and simulating a surveillance system that monitors and reports on the health status and performance of an armored fighting vehicle via an Unmanned Aerial Vehicle (UAV). The objective of this template is to demonstrate how executable SysML diagrams are used to establish a collaborative working environment between multiple platforms to better convey system behavior, modifications, and analytics for various system stakeholders

    Comprehensive Survey and Analysis of Techniques, Advancements, and Challenges in Video-Based Traffic Surveillance Systems

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    The challenges inherent in video surveillance are compounded by a several factors, like dynamic lighting conditions, the coordination of object matching, diverse environmental scenarios, the tracking of heterogeneous objects, and coping with fluctuations in object poses, occlusions, and motion blur. This research endeavor aims to undertake a rigorous and in-depth analysis of deep learning- oriented models utilized for object identification and tracking. Emphasizing the development of effective model design methodologies, this study intends to furnish a exhaustive and in-depth analysis of object tracking and identification models within the specific domain of video surveillance

    ANALYSIS AND ASSESSMENT OF LETHALITY AND SURVIVABILITY FOR THE MARINE LITTORAL REGIMENT

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    As the Marine Corps activates the Marine Littoral Regiment (MLR) to serve as the joint force’s reconnaissance and counter-reconnaissance effort, questions abound regarding the MLR’s ability to provide a persistent and lethal presence well inside the reach of our adversaries’ advanced long-range precision fires. In this study, the author uses agent-based combat simulations to inform future force design decisions, live-force experimentation, and tactics. The simulated scenario imagines a future MLR conducting sea control operations in the littorals of the Western Pacific against a peer naval threat. This research investigates the effect that a guard force of autonomous and/or semi-autonomous surface vessels, operating as the guard force of the MLR’s defense in depth, has on the survivability and lethality of the MLR’s land-based anti-ship missile platforms. Summary statistics generated by the simulation indicate that the future battlefield will see high losses on both sides. However, based on the results of 27,200 simulated engagements, this study finds that an MLR using a guard force of armed and unarmed “scouts” as described above can inflict a prohibitively high and unsustainable cost on an enemy naval force.Outstanding ThesisMajor, United States Marine CorpsApproved for public release. Distribution is unlimited

    A Systems Architectural Model for Man-Packable/Operable Intelligence, Surveillance, and Reconnaissance Mini/Micro Aerial Vehicles

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    With the increase in both technology push and operational pull of mini/micro aerial vehicles (MAVs) within DoD organizations, an understanding of their interactions and capabilities is necessary. Many MAVs have already been developed for a specific usage and much speculation has been made on their future uses. Despite the growth of MAVs, there is currently no overarching systems architecture which would envelop and guide the DoD\u27s MAV development efforts. The goal of this thesis is to apply sound systems engineering principals to develop a MAV architectural model describing their use in three separate but closely related mission areas: Over-the-Hill-Reconnaissance, Battle Damage Information, and Local Area Defense. This thesis focuses on single-man packable/operable MAVs utilized by small ground units synonymous with special operations forces. The three mission areas are combined to define a single overarching Intelligence, Surveillance, and Reconnaissance (ISR) MAV architecture. This architecture focuses on the current state of ISR MAVs and provides a baseline current capability. From this architecture, areas of interest relating to MAVs and their use in the DoD are discussed, focusing on enhancing both current and future capabilities of MAVs

    Video Surveillance Analysis as a Context for Embedded Systems and Artificial Intelligence Education

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    Video surveillance analysis is an exciting, active research area and an important industry application. It is a multidisciplinary field that draws on signal processing, embedded systems, and artificial intelligence topics, and is well suited to motivate student engagement in all of these areas. This paper describes the benefits of the convergence of these topics, presents a versatile video surveillance analysis process that can be used as the basis for many investigations, and presents two template exercises in tracking detected targets and in evaluating runtime efficiency. The processing chain consists of detecting changes in a scene and locating and characterizing the resulting targets. The analysis is illustrated for targets in outdoor scenes using a variety of classification features. Also, sample code for processing is included

    Development of a Concept of Operations for a Counter-Swarm Scenario

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    Report on the evaluation of surveillance systems relevant to zoonotic diseases in Kenya, 2015: A basis for design of an integrated human–livestock surveillance system

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    The Zoonoses in Livestock in Kenya (ZooLinK) is a project that seeks to enable Kenya develop an effective surveillance programme for zoonotic diseases (infectious diseases transmissible between animals and human beings). The surveillance programme will be integrated across both human and animal health sectors. To achieve this goal the project will work in close collaboration with Kenyan government departments in responsible for animal and human health. As a prelude to the start of the project, an evaluation of the existing surveillance systems for human and animal health was carried out. The evaluation focused on the national surveillance system and the systems at the western part of Kenya (Busia county, Kakamega county and Bungoma county) where the initial programme will be developed. In conducting the evaluation the investigators used key informant interviews, focused group discussion participant questionnaires, audio recordings and observation for data collection. Data analysis for the qualitative data focused on generating themes or theory around the responses obtained in the key informants interviews and focused group discussions. Univariate analysis was performed by use of simple proportions in calculation for surveillance system attributes like sensitivity, completeness, PVP and Timeliness for the human health surveillance systems. The findings of the evaluation revealed that there was poor linkage between animal health surveillance and the human health surveillance systems. None of the systems had surveillance structures dedicated to zoonotic diseases. Most practitioners used clinical signs for diagnosis of diseases with little reference to acceptable case definitions. Laboratory diagnosis in animal health services focused more on suspected notifiable diseases as opposed to being a standard operating procedure for diagnosis. In Human health services the health care facilities that had laboratory within the facility conducted laboratory diagnosis for cases referred by the clinicians. However, some clinicians preferred using clinical signs for diagnosis to avoid the wait or turn-around time in the laboratory. For effective surveillance of zoonoses to be realized it would be advisable to establish surveillance structures specific to zoonoses and the necessary resources allocated to the surveillance activities. In addition, an integrated approach that incorporated both human and animal disease surveillance should be employed in the surveillance of zoonoses
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