Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
— 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, ...
A common problem encountered in signboard recognition is the perspective distortion of characters. In this paper, we propose a method which is able to directly recognize character...
Semantic interoperability between heterogeneous sources of information is significant problems because of the number growing of sources of information available on the Web. The use...
Abstract. We present a new shape descriptor for measuring the similarity between shapes and exploit it in graphical object recognition and retrieval. By statistically integrating t...