In this paper, we present a probabilistic formulation of kernel-based tracking methods based upon maximum likelihood estimation. To this end, we view the coordinates for the pixel...
Quang Anh Nguyen, Antonio Robles-Kelly, Chunhua Sh...
We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
Recognition using appearance features is confounded by
phenomena that cause images of the same object to look different,
or images of different objects to look the same. This
ma...
Ali Farhadi, Mostafa Kamali Tabrizi, Ian Endres, D...
This paper summarizes our experience with introducing feature modelling into several product lines within Siemens. Feature models are used for solving various tasks in the product ...
Christa Schwanninger, Iris Groher, Christoph Elsne...