We propose a novel approach to designing algorithms for
object tracking based on fusing multiple observation models.
As the space of possible observation models is too large
for...
We describe an accurate and robust method of locating facial features. The method utilises a set of feature templates in conjunction with a shape constrained search technique. The...
This paper presents a visual particle filter for tracking a variable number of humans interacting in indoor environments, using multiple cameras. It is built upon a 3-dimensional,...
Recognizing categories of articulated objects in real-world scenarios is a challenging problem for today's vision algorithms. Due to the large appearance changes and intra-cla...
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...