Abstract--In this paper, we analyze the computational challenges in implementing particle filtering, especially to video sequences. Particle filtering is a technique used for filte...
Aswin C. Sankaranarayanan, Ankur Srivastava, Rama ...
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
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...
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
This paper presents two techniques for improving human body tracking within the particle filtering scheme. Both techniques explore the use of auxiliary measurements. The first tec...