Although not commonly used, correlation filters can track complex objects through rotations, occlusions and other distractions at over 20 times the rate of current state-ofthe-ar...
David Bolme, J Ross Beveridge, Bruce Draper, Yui M...
Sequential importance sampling (SIS), also known as particle filtering, has drawn increasing attention recently due to its superior performance in nonlinear and non-Gaussian dynam...
Yan Zhai, Mark B. Yeary, Joseph P. Havlicek, Jean-...
Particle tracking in liquid and gaseous fluids is a very useful technique to better understand flow dynamics. In this paper, we develop a novel algorithm to track a dense collecti...
Bruno Jobard, Gordon Erlebacher, M. Yousuff Hussai...
This paper proposes a method of visualizing and measuring evolution in Artificial Life simulations. The evolving population of agents is treated as a dynamical system. The propose...
We propose a particle filtering-based visual tracker, in which the affine group is treated as the state. We first develop a general particle filtering algorithm that explicitly tak...