We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
We present a method for visual classification of actions and events captured from an egocentric point of view. The method tackles the challenge of a moving camera by creating defor...
— We present an algorithm for learning 3D object models from partial object observations. The input to our algorithm is a sequence of 3D laser range scans. Models learned from th...
Michael Ruhnke, Bastian Steder, Giorgio Grisetti, ...
Aging has considerable visual effects on the human face and is difficult to simulate using a universally-applicable global model. In this paper, we focus on the hypothesis that th...
The phenomenal growth of video on the web and the increasing sparseness of meta information associated with it forces us to look for signals from the video content for search/info...
Ming Zhao 0003, Jay Yagnik, Hartwig Adam, David Ba...