Publications

Export 23 results:
[ Author(Asc)] Title Type Year
Filters: Author is Björn Andres  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
A
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., The Lazy Flipper: Efficient Depth-Limited Exhaustive Search in Discrete Graphical Models, in Computer Vision - {ECCV} 2012 - 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part {VII}, 2012.PDF icon Technical Report (446.28 KB)
B. Andres, Automated Segmentation of Large 3D Images of Nervous Systems Using a Higher-order Graphical Model. University of Heidelberg, 2011.
B. Andres, Model Selection in Optical Flow-Based Motion Estimation by Means of Residual Analysis, University of Heidelberg, 2007.
B. Andres, Hamprecht, F. A., and Garbe, C. S., Selection of Local Optical Flow Models by Means of Residual Analysis, in Pattern Recognition, 2007, vol. 4713, pp. 72-81.PDF icon Technical Report (229.64 KB)
B. Andres, Köthe, U., Bonea, A., Nadler, B., and Hamprecht, F. A., Quantitative Assessment of Image Segmentation Quality by Random Walk Relaxation Times, in Pattern Recognition. 31st DAGM Symposium, Jena, Germany, September 9-11, 2009. Proceedings, 2009, vol. 5748, pp. 502-511.PDF icon Technical Report (3.08 MB)
B. Andres, Köthe, U., Helmstaedter, M., Denk, W., and Hamprecht, F. A., Segmentation of SBFSEM Volume Data of Neural Tissue by Hierarchical Classification, in Pattern Recognition. 30th DAGM Symposium Munich, Germany, June 10-13, 2008. Proceedings, 2008, vol. 5096, pp. 142-152.PDF icon Technical Report (1.21 MB)
B. Andres, Köthe, U., Kröger, T., and Hamprecht, F. A., How to Extract the Geometry and Topology from Very Large 3D Segmentations, ArXiv e-prints, 2010.PDF icon Technical Report (1.44 MB)
B. Andres, Köthe, U., Kröger, T., and Hamprecht, F. A., Runtime-Flexible Multi-dimensional Views and Arrays for C++98 and C++0x, ArXiv e-prints, 2010.PDF icon Technical Report (415.54 KB)
B. Andres, Köthe, U., Kröger, T., Helmstaedter, M., Briggmann, K. L., Denk, W., and Hamprecht, F. A., 3D Segmentation of SBFSEM Images of Neuropil by a Graphical Model over Supervoxel Boundaries, Medical Image Analysis, vol. 16 (2012), pp. 796-805, 2012.PDF icon Technical Report (20.85 MB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in ICCV, Proceedings, 2011, pp. 2611 - 2618.PDF icon Technical Report (8.18 MB)
B. Andres, Kappes, J. H., Köthe, U., and Hamprecht, F. A., The Lazy Flipper: MAP Inference in Higher-Order Graphical Models by Depth-limited Exhaustive Search, ArXiv e-prints, 2010.PDF icon Technical Report (625.06 KB)
B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010, pp. 353-362.
B. Andres, Kondermann, C., Kondermann, D., Köthe, U., Hamprecht, F. A., and Garbe, C. S., On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation, Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, pp. 1-6, 2008.PDF icon Technical Report (1.58 MB)
B. Andres, Kröger, T., Briggmann, K. L., Denk, W., Norogod, N., Knott, G. W., Köthe, U., and Hamprecht, F. A., Globally Optimal Closed-Surface Segmentation for Connectomics, in ECCV 2012. Proceedings, Part 3, 2012, pp. 778-791.PDF icon Technical Report (2.72 MB)
B. Andres, Model Selection in Optical Flow-Based Motion Estimation by Means of Residual Analysis, University of Heidelberg, 2007.
B. Andres, Garbe, C. S., Schnörr, C., and Jähne, B., Selection of local optical flow models by means of residual analysis, in Proceedings of the 29th DAGM Symposium on Pattern Recognition, 2007, p. 72--81.
B. Andres, Kondermann, C., Kondermann, D., Hamprecht, F. A., and Garbe, C. S., On errors-in-variables regression with arbitrary covariance and its application to optical flow estimation, in IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2008, 2008, p. 1--6.
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models, in ECCV 2012, 2012.PDF icon Technical Report (532.64 KB)
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in Proceedings of ICCV, 2011.PDF icon Technical Report (2.95 MB)
B. Andres, Kappes, J. H., Köthe, U., Schnörr, C., and Hamprecht, F. A., An Empirical Comparison of Inference Algorithms for Graphical Models with Higher Order Factors Using OpenGM, in Pattern Recognition, Proc.~32th DAGM Symposium, 2010.PDF icon Technical Report (218.43 KB)
B. Andres, Beier, T., and Kappes, J. H., OpenGM: A C++ Library for Discrete Graphical Models, ArXiv e-prints, 2012.
B. Andres, Kappes, J. Hendrik, Beier, T., Köthe, U., and Hamprecht, F. A., The Lazy Flipper: Efficient Depth-limited Exhaustive Search in Discrete Graphical Models, in ECCV 2012, 2012.
B. Andres, Kappes, J. H., Beier, T., Köthe, U., and Hamprecht, F. A., Probabilistic Image Segmentation with Closedness Constraints, in Proceedings of ICCV, 2011.