Color-based trackers recently proposed in [3, 4, 5] have been proved robust and versatile for
a modest computational cost. They are especially appealing for tracking tasks where the …

Visual tracking, in essence, deals with non-stationary data streams that change over time.
While most existing algorithms are able to track objects well in controlled environments, they …

Color can provide an efficient visual feature for tracking non-rigid objects in real-time.
However, the color of an object can vary over time dependent on the illumination, the visual …

Robust visual tracking has become an important topic in the field of computer vision. The
integration of cues such as color, edge strength and motion has proved to be a promising …

A new, exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic
mechanisms are attractive because they handle fusion of information, especially temporal …

The use of adaptive Gaussian mixtures to model the colour distributions of objects is
described. These models are used to perform robust, real-time tracking under varying …

An important issue in tracking is how to incorporate an appropriate degree of adaptivity into
the observation model. Without any adaptivity, tracking fails when object properties change …

This paper presents a multi-view tracker, meant to operate in smart rooms that are equipped
with multiple cameras. The cameras are assumed to be calibrated. In particular, we …

As an object moves through the field of view of a camera, the images of the object may
change dramatically. This is not simply due to the translation of the object across the image …

This paper presents visual cues for object tracking in video sequences using particle
filtering. A consistent histogram-based framework is developed for the analysis of colour …