Browsing by Author "Holtzhausen, Petrus Jacobus"
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- ItemIdentity confidence estimation of manoeuvring aircraft(Stellenbosch : University of Stellenbosch, 2006-12) Holtzhausen, Petrus Jacobus; Herbst, B. M.; Du Preez, J. A.; Wolfaardt, P. J.; University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.A radar system observes an aircraft once during each scan of the airspace, and uses these observations to construct a track representing a possible route of the aircraft. However when aircraft interact closely there is the possiblility of confusing the identities of the tracks. In this thesis multiple hypothesis techniques are applied to extract an identity confidence from a track, given a set of possible tracks and observations. The system utilises numerous estimation filters internally and these are investigated and compared in detail. The Identity Confidence algorithm is tested using a developed radar simulation system, and evaluated sucessfully against a series of benchmark tests.
- ItemVideo Surveillance Incorporating Pan-Tilt-Zoom Cameras(Stellenbosch : Stellenbosch University, 2015-03) Holtzhausen, Petrus Jacobus; Herbst, B. M.; Crnojevic, Vladimir; Brink, Willie; Stellenbosch University. Faculty of Science. Department of Applied MathematicsENGLISH ABSTRACT : When trespassers target businesses and homes, outdoor spaces are typically the first point of illegal entry. Camera systems can help secure these environments, but typically many cameras are needed to cover large areas. In practice most camera systems are only used to review events after they have happened. It is however possible to do much more, and we explore the paradigm of active monitoring where cameras detect trespassers and give visual verification of the alarm. This detection needs to be resilient to weather effects and other environmental noise, while running in real-time on high resolution video sequences. Our goal is to replace multiple static cameras with a single Pan-Tilt-Zoom (PTZ) camera that can monitor expansive terrain. These cameras can survey, detect and zoom in on objects of interest. We develop and implement a robust, real-time algorithm based on an interaction framework between an illumination invariant and a color based background model. We also developed and implemented a novel technique where we use optical flow motion vectors to determine the size and shape of the spatial Gaussian kernels in non parametric models. Although computationally more expensive we demonstrate these more sophisticated models can be more robust. These ideas are adapted for PTZ cameras, exploiting their pan, tilt and zoom capabilities. We apply background modeling on panorama images that inform PTZ camera movement. By this we discuss the construction of a system that secures perimeters using zooming camera analytics.