Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
This paper analyses the possibilities of integrating different technological and knowledge representation techniques for the development of a framework for the remote control of mu...
Dale Dzemydiene, Antanas Andrius Bielskis, Arunas ...
We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and e...
Non-rigid object detection and articulated pose estimation
are two related and challenging problems in computer
vision. Numerous models have been proposed over the
years and oft...
Mykhaylo Andriluka (TU Darmstadt), Stefan Roth (TU...
This paper presents an efficient and homogeneous paradigm for automatic acquisition and recognition of nonparametric shapes. Acquisition time varies from linear to cubic in the nu...