Biblio

Export 218 results:
Author Title [ Type(Asc)] Year
Journal Article
Denker, K., & Umlauf G. (2011).  An accurate real-time multi-camera matching on the GPU for 3d reconstruction. Journal of WSCG. 19, 9-16.PDF icon RealTimeMultiCamera.pdf (770.39 KB)
Berlin, C., Adomeit S., Grover P., Dreischarf M., Dürr O., & Obid P. (2022).  140. Automated measurement technique for coronal parameters using a novel artificial intelligence algorithm: an independent validation study on 100 preoperative AP spine X-rays. The Spine Journal. 22, S74.
Journal
Rohrbach, J., Rainhard T., Sick B., & Dürr O. (2019).  Bone erosion scoring for rheumatoid arthritis with deep convolutional neural networks.
Conference Proceedings
Danhof, M., Schneider T., Laube P., & Umlauf G. (2015).  A Virtual-Reality 3d-Laser-Scan Simulation. BW-CAR| SINCOM. 68.
Hake, F., Hermann M., Alkhatib H., Hesse C., Holste K., Umlauf G., et al. (2020).  Damage Detection for Port Infrastructure by Means of Machine-Learning-Algorithms. FIG Working Week 2020. PDF icon Fig2020.pdf (876.57 KB)
Griesser, D., Dold D., Umlauf G., & Franz M. O. (2020).  CNN-Based Monocular 3D Ship Detection Using Inverse Perspective. Global Oceans.
Conference Paper
Franz, M. O., Hengstenberg R., & Krapp H. G. (1998).  VS-neurons as matched filters for self-motion-induced optic flow fields. (Elsner, N., & Wehner R., Ed.).{New Neuroethology on the Move}. II, 419.
Schall, M., Sacha D., Stein M., Franz M. O., & Keim D. A. (2018).  Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition. Visualization in Data Science (VDS at IEEE VIS) 2018. PDF icon Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.pdf (1.03 MB)
Griesser, D., Umlauf G., & Franz M. O. (2023).  Visual Pitch and Roll Estimation For Inland Water Vessels. IEEE International Conference on Robotics and Automation (ICRA). 1961-1967.
Mallot, H. A., Franz M. O., Schölkopf B., & Bülthoff H. H. (1997).  The view-graph approach to visual navigation and spatial memory. (Gerstner, W., Germond A., Hasler M., & Nicoud J.-D., Ed.).{Proc. of the 7th Intl. Conf. on Artificial Neural Networks (ICANN 97)}. 1327, 751 – 756.PDF icon Mallot et al._1997_The view-graph approach to visual navigation and spatial memory.pdf (212.16 KB)
Lehner, B., Umlauf G., & Hamann B. (2008).  Video compression using data-dependent triangulations. (Xiao, Y., & E. Thij ten., Ed.).Computer Graphics and Visualization '08. PDF icon VideoComprTriang.pdf (177.45 KB)
Ginkel, I., & Umlauf G. (2007).  Tuning subdivision algorithms using constrained energy minimization. (Martin, R., Sabin M., & Winkler J., Ed.).Mathematics of Surfaces XII. PDF icon SubEnergyOpt.pdf (828.98 KB)
Prautzsch, H., & Umlauf G. (1999).  Triangular G^2 splines. (Laurent, P.-L., Sablonniere P., & Schumaker L.L., Ed.).Curve and Surface Design. PDF icon TriG2Splines.pdf (393.87 KB)
Lehner, B., Umlauf G., Hamann B., & Ustin S. (2006).  Topographic distance functions for interpolation of meteorological data. (Hagen, H., Kerren A., & Dannenmann P., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. PDF icon TopoDistFunc.pdf (2.27 MB)
Umlauf, G. (2004).  A technique for verifying the smoothness of subdivision schemes. (Lucian, M.L., & Neamtu M., Ed.).Geometric Modeling and Computing: Seattle 2003. PDF icon subSchemes.pdf (110.4 KB)
Hermann, M., Griesser D., Gundel B., Dold D., Umlauf G., & Franz M. O. (2022).  Targetless Lidar-camera registration using patch-wise mutual information. International Conference on Information Fusion. PDF icon mir_reg_patch.pdf (9.58 MB)
Denker, K., & Umlauf G. (2011).  Survey on benchmarks for a GPU based multi camera stereo matching algorithm. Visualization of Large and Unstructured Data Sets - Applications in Geospatial Planning, Modeling and Engineering (IRTG 1131 Workshop. PDF icon BenchmarkStereoMatching.pdf (3.63 MB)
Lehner, B., Umlauf G., & Hamann B. (2007).  Survey of techniques for data-dependent triangulations. (Hagen, H., Hering-Bertram M., & Garth C., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. PDF icon TriangColorImg.pdf (3.64 MB)
Caputo, M., Denker K., Franz M. O., Laube P., & Umlauf G. (2015).  Support Vector Machines for Classification of Geometric Primitives in Point Clouds. (Boissonnat, J-D., Cohen A., Gibaru O., Gout C., Lyche T., Mazure M-L., et al., Ed.).Curves and Surfaces, 8th International Conference, Paris 2014. 80-95.PDF icon Caputo et al_2015_Support vector machines for classification of geometric primitives in point clouds.pdf (2.64 MB)
Staedtgen, M., Hahn S., Franz M. O., & Spitzer M. (2000).  Subliminale Darbietung verkehrsrelevanter Information in Kraftfahrzeugen. (Bülthoff, H. H., Gegenfurtner K. R., & Mallot H. A., Ed.).{Proc. 3. Tübinger Wahrnehmungskonferenz (TWK 20009)}. 98.
Le, P. H. D., Graf D., & Franz M. O. (2013).  Steganalysis in the presence of watermarked images. {Proc. 9th Intl. Conf. on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP- 2013)}. 513–517.PDF icon Le, Graf, Franz_2013_Steganalysis in the Presence of Watermarked Images.pdf (1.07 MB)
Yovel, Y., Stilz P., Franz M. O., & Schnitzler H.-U. (2008).  The statistics of plant echoes as perceived by echolocating bats. {Proc. of the Computational and Systems Neuroscience Meeting 2008 (COSYNE 2008)}.
Yovel, Y., Stilz P., Franz M. O., & Schnitzler H.-U. (2008).  The statistics of plant echoes as perceived by echolocating bats. {ASA Meeting Paris}.
Yovel, Y., Franz M. O., Stilz P., & Schnitzler H.-U. (2008).  The statistics of plant echoes as perceived by echolocating bats. {Acoustics 08, Paris, SBN 978-2-9521105-4- 9 - EAN 9782952110549}. 123, DVD Proc..
Lukic, Y., Vogt C., Dürr O., & Stadelmann T. (2016).  Speaker Identification and Clustering using Convolution Neural Networks. IEEE International workshop on Machine Learning for Signal Processing.

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