Nishan Canagarajah

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In this paper we investigate object tracking in video sequences by using the potential of particle filtering to process features from video frames. A particle filter (PF) and a Gaussian sum particle filter (GSPF) are developed based upon multiple information cues, namely colour and texture, which are described with highly nonlinear models. The algorithms(More)
A perceptually optimised approach to sign language video coding is presented. The proposed approach is based on the results (included) of an eye tracking study in the visual attention of sign language viewers. Results show reductions in bit rate of over 30% with very good subjective quality. Introduction: Coding of image sequences will always result in some(More)
In this paper we describe a system that embarks upon the problem of efficient video processing and representation for automatic semantic classification and modelling for indexing and retrieval of large multimedia databases. The major focus of the system is the integration of a large-scale wildlife digital video archive with manually annotated semantic(More)
Object tracking in video sequences is a challenging task and has various applications. We review particle filtering techniques for tracking single and multiple moving objects in video sequences, by using different features such as colour, shape, motion, edge and sound. Pros and cons of these algorithms are discussed along with difficulties that have to be(More)
This paper presents a particle filtering algorithm for multiple object tracking. The proposed particle filter (PF) embeds a data association technique based on the joint probabilistic data association (JPDA) which handles the uncertainty of the measurement origin. I. Introduction Tracking a group of targets in video sequences has many surveillance(More)
This paper considers mobility tracking in wireless communication networks based on received signal strength indicator measurements. Mobility tracking involves on-line estimation of the position and speed of a mobile unit. Mobility tracking is formulated as an estimation problem of a hybrid system consisting of a base state vector and a modal state vector.(More)
This paper describes a new methodology for multimodal image fusion based on non-Gaussian statistical modelling of wavelet coefficients of the input images. The use of families of generalised Gaussian and alpha-stable distributions for modelling image wavelet coefficients is investigated and methods for estimating distribution parameters are proposed.(More)
This chapter describes a new methodology for multimodal image fusion based on non-Gaussian statistical modelling of wavelet coefficients of the input images. The use of families of generalised Gaussian and alpha-stable distributions for modelling image wavelet coefficients is investigated and methods for estimating distribution parameters are proposed.(More)