The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Many vision tasks can be formulated as partitioning an adjacency graph through optimizing a Bayesian posterior probability p defined on the partition-space. In this paper two appr...
In this paper, we introduce a novel discriminative feature space which is efficient not only for face detection but also for recognition. The face representation is based on local...
This paper describes a head-tracking algorithm that is based on recognition and correlation-based weighted interpolation. The input is a sequence of 3D depth images generated by a...
Multibody factorization algorithms [2, 1, 16] give an elegant and simple solution to the problem of structure from motion even for scenes containing multiple independent motions. ...