Isomap Tracking with Particle Filtering

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Isomap Tracking with Particle Filtering
The problem of tracking involves challenges like in-plane and out-of-plane rotations, scaling, variations in ambient light and occlusions. In this paper we look at the problem of tracking a person's head and also estimating its pose in each frame. Robust tracking can be achieved by reducing the dimensionality of high-dimensional training data and using the recovered low-dimensional structure to estimate the state of an object at every time-step with recursive Bayesian filtering. Isometric feature mapping, also known as Isomap, provides an unsupervised framework to find the true degrees of freedom in high-dimensional input data like a person's head with varying poses. After the data has been reduced to lower dimensions a particle filter can be used to track and at the same time approximate the pose of a person's head in any image sequence. Isomap tracking with particle filtering is capable of handling rapid translation and out-of-plane rotation of a person's head wi...
Nikhil Rane, Stanley T. Birchfield
Added 21 Oct 2009
Updated 21 Oct 2009
Type Conference
Year 2007
Where ICIP
Authors Nikhil Rane, Stanley T. Birchfield
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