ITC/USA 2006 Conference Proceedings / The Forty-Second Annual International Telemetering Conference and Technical Exhibition / October 23-26, 2006 / Town and Country Resort & Convention Center, San Diego, California / Drivers’ visibility is an area of automobile safety that has seen very limited improvement over the past several decades. Limited visibility is responsible for many car accidents all across America. Mirrors require constant readjustment, and are easily blocked. There is currently a lot of interest in ways to reduce or eliminate all mirrors on a car, and one such method is through a wide-angle network of cameras mounted on the vehicle’s rear. Using real-time video processing, the data from several cameras can be spliced together, and displayed on a vehicle’s dashboard in an intuitive, easy to understand fashion that a driver can quickly see without having to turn away from the road. This has extensive application to light armored vehicles in the military, as well as to automotive designers today.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / The deployment of network-based airborne instrumentation systems is leading to cost-efficient replacement of legacy instrumentation systems. One application of airborne data acquisition that has been developed and maintained separately from traditional avionics and orange-wire data acquisition systems is high-speed camera packages. The development of network-based instrumentation systems has led to an opportunity to unify these two previously distinct airborne data acquisition activities. This paper describes the range-video network-based instrumentation system (rNET) being implemented by the 46th Test Wing, 846th Test Support Squadron at Eglin Air Force Base, FL to replace the existing Airborne Separation Video System (ASVS).

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / The deployment of network-based airborne instrumentation is leading to cost efficient replacement of legacy systems. One application of airborne instrumentation systems that has to this point been developed and maintained separately from traditional avionics and orange-wire data acquisition systems is video and imagery. The development of network-based video and imagery systems has led to an opportunity to unify these two previously distinct airborne data acquisition activities using standards for plug-n-play interoperability across airframes and organizations. This paper describes standards based network-based video and imagery instrumentation systems which, are being implemented to replace existing proprietary systems.

published_or_final_version / Computer Science and Information Systems / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / abstract / Computer Science / Master / Master of Philosophy

In the tracking of a moving ground target by small unmanned air vehicle (UAV) via camera vision, the target position and motion cannot be measured directly. Two different types of filters were assessed for their ability to estimate target motion, namely target velocity, directional heading on flat ground and distance from the UAV to target. The first filter is a nonlinear deterministic filter with stability guarantee. The second filter is based on nonlinear Kalman Filter technique. The application and performance of these two filters are presented, for simulated vision based target tracking.

This thesis was part of the ongoing research conducted at the Naval Postgraduate School to achieve greater collaboration between heterogeneous autonomous vehicles. The research addresses optimal control issues in the collaboration between an Unmanned Aerial Vehicle (UAV) and Autonomous Ground Vehicles (AGV). The scenario revolves around using the camera onboard the UAV to extend the effective field of view of the AGV. For military operations, this could be helpful in improving security for convoys and riverine patrols. There were three main problems addressed in this thesis. The first problem dealt with the design of a UAV control law that takes into consideration the relative speed differences between the UAV and the AGV. The UAV was assumed to have a greater speed compared to the AGV in this thesis. The second was the keystone field of view projection effect of the UAVâ s onboard camera onto the earth. The image captured by the camera was distorted due to the view angle of the camera from a high elevation. The third problem addressed was control of the location of the UAV to ensure the reliability of the communication network between the UAV and the AGV. The communication was assumed to be a linear function of the relative positions of the UAV and the AGV.

The ubiquitous nature of CCTV Surveillance cameras means substantial amounts of data being generated. In case of an investigation, this data must be manually browsed and analysed in search of relevant information for the case. As an example, it took more than 450 detectives to examine the hundreds of thousands of hours of videos in the investigation of the 2011 London Riots: one of the largest the London's MET police has ever seen. Anything that can help the security forces save resources in investigations such as this, is valuable. Consequently, automatic analysis of surveillance scenes is a growing research area. One of the research fronts tackling this issue, is the semantic understanding of the scene. In this, the output of computer vision algorithms is fed into Semantic Frameworks, which combine all the information from different sources and try to reach a better knowledge of the scene. However, representing and reasoning with imprecise and uncertain information remains an outstanding issue in current implementations. The Demspter-Sha er (DS) Theory of Evidence has been proposed as a way to deal with imprecise and uncertain information. In this thesis we use it for the main contributions. In our rst contribution, we propose the use of the DS theory and its Transferable Belief Model (TBM) realisation as a way to combine Bayesian priors, using the subjectivist view of the Bayes' Theorem, where the probabilities are beliefs. We rst compute the a priori probabilities of all the pair of events in the model. Then a global potential is created for each event using the TBM. This global potential will encode all the prior knowledge for that particular concept. This has the bene t that when this potential is included in a knowledge base because it has been learned, all the knowledge it entails comes with it. We also propose a semantic web reasoner based on the TBM. This reasoner consists of an ontology to model any domain knowledge using the TBM constructs of Potentials, Focal Elements, and Con gurations. The reasoner also consists of the implementations of the TBM operations in a semantic web framework. The goal is that after the model has been created, the TBM operations can be applied and the knowledge combined and queried. These operations are computationally complex, so we also propose parallel heuristics to the TBM operations. This allows us to apply this paradigm on problems of thousands of records. The nal contribution, is the use of the TBM semantic framework with the method to combine the prior knowledge to detect riots on CCTV footage from the 2011 London riots. We use around a million and a half manually annotated frames with 6 di erent concepts related to the riot detection task, train the system, and infer the presence of riots in the test dataset. Tests show that the system yields a high recall, but a low precision, meaning that there are a lot of false positives. We also show that the framework scales well as more compute power becomes available.

Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.