Doctoral Degrees (Mathematical Sciences)

Permanent URI for this collection

https://scholar.sun.ac.za/handle/10019.1/852

Browse

Browsing Doctoral Degrees (Mathematical Sciences) by browse.metadata.advisor "Du Preez, J."

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Stochastic visual tracking with active appearance models
    (Stellenbosch : University of Stellenbosch, 2009-12) Hoffmann, McElory Roberto; Herbst, B. M.; Hunter, K.; Van Zijl, L.; Du Preez, J.; University of Stellenbosch. Faculty of Engineering. Dept. of Mathematical Sciences. Applied Mathematics.
    ENGLISH ABSTRACT: In many applications, an accurate, robust and fast tracker is needed, for example in surveillance, gesture recognition, tracking lips for lip-reading and creating an augmented reality by embedding a tracked object in a virtual environment. In this dissertation we investigate the viability of a tracker that combines the accuracy of active appearancemodels with the robustness of the particle lter (a stochastic process)—we call this combination the PFAAM. In order to obtain a fast system, we suggest local optimisation as well as using active appearance models tted with non-linear approaches. Active appearance models use both contour (shape) and greyscale information to build a deformable template of an object. ey are typically accurate, but not necessarily robust, when tracking contours. A particle lter is a generalisation of the Kalman lter. In a tutorial style, we show how the particle lter is derived as a numerical approximation for the general state estimation problem. e algorithms are tested for accuracy, robustness and speed on a PC, in an embedded environment and by tracking in ìD. e algorithms run real-time on a PC and near real-time in our embedded environment. In both cases, good accuracy and robustness is achieved, even if the tracked object moves fast against a cluttered background, and for uncomplicated occlusions.