An "inconsistent" particle filter produces--in a statistical sense--larger estimation errors than predicted by the model on which the filter is based. Two test variables ...
Particle filters are used for hidden state estimation with nonlinear dynamical systems. The inference of 3-d human motion is a natural application, given the nonlinear dynamics of...
A new particle filter, Kernel Particle Filter (KPF), is proposed for visual tracking for multiple objects in image sequences. The KPF invokes kernels to form a continuous estimate...
In this paper we present algorithmic and architectural methodology for building Particle Filters in hardware. Particle filtering is a new paradigm for filtering in presence of n...
Aswin C. Sankaranarayanan, Rama Chellappa, Ankur S...
—This paper presents a novel application of the GPU processing power to a very computationally demanding articulated human body tracking problem in a view-based approach. This wo...