We study efficient importance sampling techniques for particle filtering (PF) when either (a) the observation likelihood (OL) is frequently multimodal or heavy-tailed, or (b) the s...
In the recent years particle filtering has been the dominant paradigm for tracking facial and body features, recognizing temporal events and reasoning in uncertainty. A major prob...
Abstract. In this paper, we consider the problem of filtering in relational hidden Markov models. We present a compact representation for such models and an associated logical par...
Luke S. Zettlemoyer, Hanna M. Pasula, Leslie Pack ...
Particle filtering algorithms can be used for the monitoring of dynamic systems with continuous state variables and without any constraints on the form of the probability distribu...
We propose algorithms for tracking the boundary contour of a deforming object from an image sequence, when the nonaffine (local) deformation over consecutive frames is large and th...
Namrata Vaswani, Yogesh Rathi, Anthony J. Yezzi, A...