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K

Kandemir, M, Rubio, J C, Schmidt, U, Wojek, C, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. Medical Image Computing and Computer-Assisted Intervention. Springer. 154--161

Technical Report (2 MB)

Kandemir, M, Rubio, J C, Schmidt, U, Welbl, J, Ommer, B and Hamprecht, F A (2014). Event Detection by Feature Unpredictability in Phase-Contrast Videos of Cell Cultures. MICCAI. Proceedings. Springer. 154-161

Paper (2 MB)

A

Antic, B and Ommer, B (2014). Learning Latent Constituents for Recognition of Group Activities in Video. Proceedings of the European Conference on Computer Vision (ECCV) (Oral). Springer. 33--47

Technical Report (4.54 MB)

M

Monroy, A, Bell, P and Ommer, B (2014). Morphological Analysis for Investigating Artistic Images. Image and Vision Computing. Elsevier. 32 414--423

Technical Report (2.86 MB)

T

Takami, M, Bell, P and Ommer, B (2014). Offline Learning of Prototypical Negatives for Efficient Online Exemplar SVM. Winter Conference on Applications of Computer Vision. IEEE. 377--384. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6836075

E

Eigenstetter, A, Takami, M and Ommer, B (2014). Randomized Max-Margin Compositions for Visual Recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. IEEE. 3590--3597

Technical Report (8.01 MB)

A

Arnold, M, Bell, P and Ommer, B (2013). Automated Learning of Self-Similarity and Informative Structures in Architecture. Scientific Computing & Cultural Heritage

Antic, B, Milbich, T and Ommer, B (2013). Less is More: Video Trimming for Action Recognition. Proceedings of the IEEE International Conference on Computer Vision, Workshop on Understanding Human Activities: Context and Interaction. IEEE. 515--521

Technical Report (984.89 KB)

M

Monroy, A, Bell, P and Ommer, B (2013). A Morphometric Approach to Reception Analysis of Premodern Art. Scientific Computing & Cultural Heritage

Technical Report (17.75 MB)

B

Bell, P, Schlecht, J and Ommer, B (2013). Nonverbal Communication in Medieval Illustrations Revisited by Computer Vision and Art History. Visual Resources Journal, Special Issue on Digital Art History. Taylor & Francis. 29 26--37. http://www.tandfonline.com/doi/abs/10.1080/01973762.2013.761111

G

Garbe, C S and Ommer, B (2013). Parameter Estimation in Image Processing and Computer Vision. Model Based Parameter Estimation: Theory and Applications. Springer. 311--334

Technical Report (928 KB)

O

Ommer, B (2013). The Role of Shape in Visual Recognition. Shape Perception in Human Computer Vision: An Interdisciplinary Perspective. Springer. 373--385

Technical Report (8.18 MB)

Y

Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2013). Towards a Computer-based Understanding of Medieval Images. Scientific Computing & Cultural Heritage. Springer. 89--97. http://link.springer.com/chapter/10.1007/978-3-642-28021-4_10

M

Monroy, A and Ommer, B (2012). Beyond Bounding-Boxes: Learning Object Shape by Model-driven Grouping. IEEE Transactions on Pattern Analysis and Machine Intelligence. Springer. 7574 582--595

Technical Report (1.58 MB)

Y

Yarlagadda, P and Ommer, B (2012). From Meaningful Contours to Discriminative Object Shape. Proceedings of the European Conference on Computer Vision. Springer. 7572 766--779

Technical Report (4.58 MB)

Yarlagadda, P, Eigenstetter, A and Ommer, B (2012). Learning Discriminative Chamfer Regularization. BMVC. Springer. 1--11. http://www.bmva.org/bmvc/2012/BMVC/paper020/paper020.pdf

E

Eigenstetter, A, Yarlagadda, P and Ommer, B (2012). Max-Margin Regularization for Reducing Accidentalness in Chamfer Matching. Proceedins of the Aian Conference on Computer Vision. Springer. 152--163

Technical Report (7.31 MB)

A

Antic, B and Ommer, B (2012). Robust Multiple-Instance Learning with Superbags. Proceedings of the Aian Conference on Computer Vision (ACCV) (Oral). Springer. 242--255

Technical Report (319.58 KB)

M

Monroy, A, Bell, P and Ommer, B (2012). Shaping Art with Art: Morphological Analysis for Investigating Artistic Reproductions. Proceedings of the European Conference on Computer Vision, Workshop on VISART. Springer. 7583 571--580

Technical Report (7 MB)

E

Eigenstetter, A and Ommer, B (2012). Visual Recognition using Embedded Feature Selection for Curvature Self-Similarity. Proceedings of the Conference on Advances in Neural Information Processing Systems. MIT Press. 377--385

Technical Report (3.27 MB)

M

Monroy, A, Eigenstetter, A and Ommer, B (2011). Beyond Straight Lines - Object Detection using Curvature. International Conference on Image Processing (ICIP). IEEE

Technical Report (2.65 MB)

S

Schlecht, J and Ommer, B (2011). Contour-based Object Detection. BMVC. 1--9

Technical Report (2.62 MB)

Schlecht, J, Carque, B and Ommer, B (2011). Detecting Gestures in Medieval Images. Proceedings of the International Conference on Image Processing. IEEE. 1309--1312

Technical Report (1.61 MB)

M

Monroy, A, Kröger, T, Arnold, M and Ommer, B (2011). Parametric Object Detection for Iconographic Analysis. Scientific Computing & Cultural Heritage. http://www.academia.edu/9439693/Parametric_Object_Detection_for_Iconographic_Analysis

Monroy, A, Carque, B and Ommer, B (2011). Reconstructing the Drawing Process of Reproductions from Medieval Images. Proceedings of the International Conference on Image Processing. IEEE. 2974--2977. https://hciweb.iwr.uni-heidelberg.de/compvis/research/manesse/

Technical Report (2.43 MB)

Y

Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2011). Top-down Analysis of Low-level Object Relatedness Leading to Semantic Understanding of Medieval Image Collections. Conference on Computer Vision and Image Analysis of Art II. 7869 61--69

Technical Report (11.06 MB)

A

Antic, B and Ommer, B (2011). Video Parsing for Abnormality Detection. Proceedings of the IEEE International Conference on Computer Vision. IEEE. 2415--2422

Technical Report (990.21 KB)

W

Wagner, J and Ommer, B (2010). Efficiently Clustering Earth Mover's Distance. Proceedins of the Aian Conference on Computer Vision. Springer. 477--488

Technical Report (841.98 KB)

O

Ommer, B and Buhmann, J M (2010). Learning the Compositional Nature of Visual Object Categories for Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence. IEEE. 32 501--516

Technical Report (2.78 MB)

Y

Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2010). Recognition and Analysis of Objects in Medieval Images. Proceedins of the Aian Conference on Computer Vision, Workshop on e-Heritage. Springer. 296--305

Technical Report (2.76 MB)

Yarlagadda, P, Monroy, A and Ommer, B (2010). Voting by Grouping Dependent Parts. Proceedings of the European Conference on Computer Vision. Springer. 6315 197--210

Technical Report (2.99 MB)

K

Keränen, S V E, DePace, A, Hendriks, C L Luengo, Fowlkes, C, Arbelaez, P, Ommer, B, Brox, T, Henriquez, C, Wunderlich, Z, Eckenrode, K, Fischer, B, Hammonds, A and Celniker, S E (2009). Computational Analysis of Quantitative Changes in Gene Expression and Embryo Morphology between Species. Evolution-The Molecular Landscape

O

Ommer, B and Malik, J (2009). Multi-scale Object Detection by Clustering Lines. Proceedings of the IEEE International Conference on Computer Vision. IEEE. 484--491

Technical Report (3.18 MB)

Ommer, B, Mader, T and Buhmann, J M (2009). Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera. International Journal of Computer Vision. Springer. 83 57--71

Technical Report (9.61 MB)

Y

Yarlagadda, P, Monroy, A, Carque, B and Ommer, B (2009). Towards a Computer-based Understanding of Medieval Images. Scientific Computing & Cultural Heritage. Springer. 89--97. http://link.springer.com/chapter/10.1007%2F978-3-642-28021-4_10#page-1

Pages