@inproceedings{GraesslDeinzerNiemann, author = {Gr{\"a}ßl, Christoph and Deinzer, Frank and Niemann, Heinrich}, title = {Continuous Parametrization of Normal Distributions for Improving the Discrete Statistical Eigenspace Approach for Object Recognition}, series = {Pattern Recognition and Information Processing}, volume = {1}, booktitle = {Pattern Recognition and Information Processing}, editor = {Krasnoproshin, V. and Ablameyko, S. and Soldek, J.}, pages = {73 -- 77}, language = {en} } @inproceedings{GraesslDeinzerMatternetal., author = {Gr{\"a}ßl, Christoph and Deinzer, Frank and Mattern, F. and Niemann, Heinrich}, title = {Improving Statistical Object Recognition Approaches by a Parameterization of Normal Distributions}, series = {6th German-Russian IAPR Workshop on Pattern Recognition and Image Understanding}, booktitle = {6th German-Russian IAPR Workshop on Pattern Recognition and Image Understanding}, pages = {38 -- 41}, language = {en} } @inproceedings{GrzegorzekDeinzerReinholdetal., author = {Grzegorzek, Marcin and Deinzer, Frank and Reinhold, Michael and Denzler, Joachim and Niemann, Heinrich}, title = {How Fusion of Multiple Views Can Improve Object Recognition in Real-World Environments}, series = {Proceedings of the Vision, Modeling, and Visualization Conference 2003}, booktitle = {Proceedings of the Vision, Modeling, and Visualization Conference 2003}, editor = {Ertl, T. and Girod, B. and Greiner, G. and Niemann, Heinrich and Seidl, H.-P. and Steinbach, E. and Westermann, R.}, isbn = {3-89838-048-3}, pages = {553 -- 560}, abstract = {In the past decades most object recognition systems were based on passive approaches. But in the last few years a lot of research was done in the field of active object recognition. In this context there are several unique problems to be solved. One of them is how to fuse a series of images that might differ in their viewpoints. In this paper we present a well-founded approach for the fusion of multiple views based on a recursive density propagation method. It uses particle filters for solving the fusion in a continuous pose space. Furthermore we will show by means of a statistical object recognition system how to integrate such systems into our fusion approach. The experimental result will show, how the fusion can improve classification rates substantial, es-pecially for difficult conditions like heterogeneous background within real world environments.}, language = {en} } @inproceedings{DeinzerDenzlerNiemann, author = {Deinzer, Frank and Denzler, Joachim and Niemann, Heinrich}, title = {Viewpoint Selection - Planning Optimal Sequences of Views for Object Recognition}, series = {Computer Analysis of Images and Patterns - CAIP 2003}, volume = {2756}, booktitle = {Computer Analysis of Images and Patterns - CAIP 2003}, editor = {Petkov, N. and Westenberg, M.}, isbn = {3-540-40730-8}, pages = {65 -- 73}, language = {en} }