The sequential importance sampling (SIS) algorithm has gained considerable popularity for its empirical success. One of its noted applications is to the binary contingency tables p...
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-...
In this paper, a new integrated particle filter is proposed for video object tracking. After particles are generated by importance sampling, each particle is regressed on the tran...
Importance Sampling is a potentially powerful variance reduction technique to speed up simulations where the objective depends on the occurrence of rare events. However, it is cru...
Abstract. The particle filter has attracted considerable attention in visual tracking due to its relaxation of the linear and Gaussian restrictions in the state space model. It is...
Chunhua Shen, Anton van den Hengel, Anthony R. Dic...