[5] ImageCLEF. Experimental Evaluation in Visual Information Retrieval
H. Muller, P. Clough, Th. Deselaers, B. Caputo (eds). Springer, September 2010.
[4] Multilingual Information Access Evaluation II: Multimedia Experiments.
Carol Peters, Theodora Tsikrika, Henning Muller, Jayashree Kalpathy-Cramer, Gareth J.F.Jones, Julio Gonzalo, Barbara Caputo (eds). Lecture notes in Computer Science, to appear, 2010.
[3] Advances in medical content-based retrieval for clinical decision support.
B. Caputo, H. Muller, T. Syeda-Mahmood, J. S. Duncan, F. Wang, J. Kalpathy-Cramer (eds). Lecture notes in Computer Science,
Vol 5853, 2009, Springer.
[2] Cognitive Vision. Proceedings of the 4th International Cognitive Vision Workshop
B. Caputo, M. Vincze (eds). Lecture notes in Computer Science, Vol 5329, 2008, Springer.
[1] A new kernel method for appearance-based object recognition: spin glass-Markov random fields.
PhD thesis, CVAP-NADA, Royal Institute of Technology, Stockholm, Sweden
[pdf]
Journals
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[17] Multi Kernel Learning with Online-Batch
Optimization.
F. Orabona, L. Jie, B. Caputo.
Multi Kernel Learning with Online-Batch
Optimization.
Journal of Machine Learning Research, accepted for publication, 2011.
[16] Using object affordances to improve object recognition.
C. Castellini, T. Tommasi, N. Noceti, F. Odone, B. Caputo.
IEEE Transaction on Autonomous Mental Development, 3 (3), 207-215, 2011.
[15] Towards Semi-Supervised Learning of Semantic Spatial Concepts.
J. Martinez-Gomez, B. Caputo.
Journal of Physical Agents, 4 (3), 2010.
[14] Melanoma Recognition using Kernel Classifiers.
E. La Torre, B. Caputo, T. Tommasi.
International Journal on Image and System Technology, 20, 316-322, 2010.
[13] A Performance Evaluation of Exact and Approximate Match Kernels for Object Recognition.
B. Caputo, L. Jie
Electronic Letters on Computer Vision and Image Analysis, 8 (3), 15-26, 2009.
[12] The More You Learn, the Less You Store: Memory-controlled Incremental SVM for
Visual Place Recognition.
A. Pronobis, L. Jie, B. Caputo.
Image and Vision Computing, Special Issue on Incremental Learning,28 (7), 1080-1097, 2010.
[11] Multi-modal Place Classification for Semantic Robot Localization.
A. Pronobis, O. Martinez-Monoz, B. Caputo, P. Jensfelt.
International Journal on Robotic Research, Special issue on Robot Vision, 29 (2-3), 298-320, 2010.
[10] A Realistic Benchmark for Robust
Vision-based Localization.
A. Pronobis, B. Caputo, P. Jensfelt, H. Christensen.
Robotics and Autonomous Systems, 58 (1), 81-96, 2010
[9] Bounded kernel-based perceptrons.
F. Orabona, J. Keshet, B. Caputo.
Journal of Machine Learning Research, 10 (2009), 2643-2666.
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[8] Online Independent Support Vector Machine.
F. Orabona, C. Castellini, B. Caputo, J. Luo, G. Sandini.
Pattern Recognition, 43 (4), 1402-1412, 2010.
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[7] Classifying materials in the real world.
B. Caputo, E. Hayman, M. J. Fritz, J.-O. Eklundh.
Image and Vision Computing, 28 (2010), 150-163.
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[6] COLD: The COsy Localization Database
A. Pronobis, B. Caputo.
International Journal on Robotic Research, 28 (5), 588-594, 2009.
[pdf]
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[5] Kernel-Class Specific Classifiers.
B. Caputo.
Electronic Letters on Computer Vision and Image Analysis, special issue on Computational Modelling of Objects Represented in Images,
7 (2): 96-109, 2008.
[pdf]
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[4] Discriminative Cue Integration for Medical
Image Annotation.
T. Tommasi, F. Orabona, B. Caputo.
Pattern Recognition Letters,
Special issue on IMageCLEF Med benchmark evaluation, 29 (15), 1996-2002, November 2008.
[pdf]
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[3] Local velocity-adapted motion events for spatio-temporal
recognition
I. Laptev, B. Caputo, C. Schultz, T. Lindeberg.
Computer Vision and Image Understanding, 108 (3), 207-229, December 2007.
[pdf]
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[2] Spin glass models of Markov random fields.
B. Caputo.
International Journal on Image System and Technology,
Special Issue on Computer Vision, 16 (5), 181-188, January 2006.
[pdf]
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[1] Analysis of Periapical Lesion Using Statistical Textural Features
and Neural Networks
B. Caputo, G. E. Gigante.
Physica Medica, Vol XVII, N. 2, 67-71, April-June 2001.
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Peer Reviewed Conference Papers
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[50] Transferring Activities: Updating Human Behavior Analysis
F. Nater*, T. Tommasi*, H. Grabner, L. Van Gool, B. Caputo. (* equal authors listed in alphabetic order)
Visual Surveillance Workshop at ICCV 2011.
[49] A Large-Scale Database of Image and Captions for Automatic Face Naming.
M. Ozcan, L. Jie, B. Caputo, V. Ferrari.
Proceedings of the British Machine Vision Conference (BMVC 2011).
[48] Towards Semi-Supervised Learning of Semantic
Spatial Concepts.
J. Martinez-Gomez, B. Caputo.
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2011).
[47]Multiclass Transfer Learning from Unconstrained Priors.
L. Jie*, T. Tommasi*, B. Caputo. (* equal authors listed in alphabetic order)
Proceedings of International Conference on Computer Vision (ICCV 2011)
[46] Object recognition using visuo-affordance maps
A. Gijsberts, T. Tommasi, G. Metta, B. Caputo.
Proceedings of the IEEE International Conference on Intelligent Robots and Systems (IROS 2010).
[pdf]
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[45] OM-2: an online multi-class multi kernel learning algorithm.
L. Jie, F. Orabona, M. Fornoni, B. Caputo, N. Cesa-Bianchi.
Proceedings of the fourth IEEE Online Learning for Computer Vision Workshop, in conjunction with CVPR 2010.
[pdf]
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[44] Online-Batch Strongly Convex Multi Kernel Learning.
F. Orabona, L. Jie, B. Caputo.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR10).
[pdf]
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[43] Safety in numbers: learning categories from few examples with multi model knowledge transfer.
T. Tommasi, F. Orabona, B. Caputo.
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR10).
[pdf]
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[42] Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation
L. Jie, B. Caputo, V. Ferrari.
Proc. NIPS 2009.
[pdf]
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[41] An online framework for learning novel concepts over multiple cues
L. Jie, F. Orabona, B. Caputo.
Proc. ACCV 2009.
[pdf]
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[40] The more you know, the less you learn: from knowledge transfer to one-shot learning of object categories
T. Tommasi, B. Caputo.
Proc. BMVC 2009.
[pdf]
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[39] You Live, You Learn, You Forget: Continuous
Learning of Visual Places with a Forgetting Mechanism.
M. M. Ullah, F. Orabona, B. Caputo.
Proc. IROS 2009, to appear.
[pdf]
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[38] Towards a theoretical framework for learning multi-modal patterns for embodied agents.
N. Noceti, B. Caputo, C. Castellini, L. Baldassarre, A. Barla, L. rosasco, F. Odone, G. Sandini.
Proc. ICIAP 2009, to appear.
[pdf]
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[37] A Theoretical Framework for Transfer of Knowledge Across Modalities in Artificial and Biological Systems.
F. Orabona, B. Caputo, A. Fillbrandt, F. W. Ohl.
Proc. ICDL 2009.
[pdf]
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[36] An SVM confidence-based approach to medical image annotation.
T. Tommasi, F. Orabona, B. Caputo.
Proc. CLEF 2008.
[pdf]
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[35] Model adaptation with least-squares SVM for adaptive hand prosthetics.
F. Orabona, C. Castellini, B. Caputo, A. E. Fiorilla, G. Sandini.
Proc. ICRA 2009.
[pdf]
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[34] The DIRAC AWEAR audio-visual platform for detection of uneypected and incongruent events.
J. Anemueller, J.-H. Bach, B. Caputo, M. Havlena, L. Jie, H. Kayser, B. Leibe, P. Motlicek, T. Oajdla, M. Pavel, A. Torli, A. Zweig, H. Hermansky.
Proc. ICMI 2008.
[pdf]
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[33] The projectron: a bounded kernel-based perceptron.
F. Orabona, J. Keshet, B. Caputo.
Proc. ICML 2008
[pdf]
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[32] Biologically Motivated Audio-Visual Cue Integration for Object Categorization.
J. Anemueller, J-H. Bach, B. Caputo, L. Jie, F. Ohl, F. Orabona, R. Vogels, D. Weinshall, A. Zweig.
Proc ICCS 2008
[pdf]
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[31] Audio-visual Object Category Detection.
J. Luo, B. Caputo, A. Zweig, D. Wheinshall, J.-H. Bach, J. Anemueller.
Proc. ICVS 2008
[pdf]
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[30] Towards Robust Place Classification for Robot Localization.
M. M. Ullah, A. Pronobis, B. Caputo, J. Luo, P. Jensfelt, H. Christensen.
Proc ICRA 2008
[pdf]
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[29] SVM-based discriminative accumulation scheme for place recognition.
A. Pronobis, O. Martinez, B. Caputo.
Proc ICRA 2008
[pdf]
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[28] Cue Integration for Medical Image Annotation.
T. Tommasi, F. Orabona, B. Caputo.
Proc CLEF 2007
[pdf]
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[27] Online incremental support vector machines for place recognition.
F. Orabona, C. Castellini, B. Caputo, J. Luo, G. Sandini.
Proc BMVC 2007 [pdf]
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[26] Confidence based cue integration for place recognition.
A. Pronobis, B. Caputo.
Proc IROS 2007 [pdf]
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[25] Incremental learning for place recognition in dynamic environments.
J. Luo, A. Pronobis, B. Caputo, P. Jensfelt.
Proc IROS 2007 [pdf]
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[24] SVM-based Transfer of Visual Knowledge Across Robotic Platforms.
J. Luo, A. Pronobis, B. Caputo.
Proc ICVS 2007
[pdf]
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[23] A Discriminative Approach to Robust Visual Place Recognition
A. Pronobis, B. Caputo, P. Jensfelt, H. Christensen.
Proc IROS 2006 [pdf]
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[22] Kernel Methods for Melanoma Recognition.
E. La Torre, T. Tommasi, B. Caputo.
Proc MIE 2006 [pdf]
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[21] Melanoma recognition using representative
and discriminative kernel classifiers.
T. Tommasi, E. La Torre, B. Caputo.
Proc CVAMIA06 [pdf]
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[20] Class-specific material categorization.
B. Caputo, E. Hayman, P. Mallikarjuna.
Proc ICCV 2005 [pdf]
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[19] Integrating representative and discriminative models for
object category detection.
M. Fritz, B. Leibe, B. Caputo, B. Schiele.
Proc ICCV 2005 [pdf]
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[18] Recognizing human actions: a local SVM approach.
C. Schuld, I. Laptev, B. Caputo.
Proc ICPR 2004 [pdf]
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[17] Object categorization via local kernels.
B. Caputo, C. Wallraven, M. E. Nilsback.
Proc ICPR 2004 [pdf]
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[16] Cue integration through discriminative accumulation.
M. E. Nilsback, B. Caputo.
Proc CVPR 2004 [pdf]
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[15] On the significance of real-world conditions for material classification.
E. Hayman, B. Caputo, M. J. Fritz, J-O.Eklund.
Proc ECCV 2004 [pdf]
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[14] Recognition with local features: the kernel recipe.
C. Wallraven, B. Caputo, A. Graf.
Proc ICCV 2003 [pdf]
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[13] How to combine color and shape information for 3D object recognition:
kernels do the trick.
B. Caputo, Gy. Dorko.
Proc NIPS 2002. [pdf]
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[12] An Ultrametric Approach to Object Recognition.
B. Caputo, Gy. Dorko, H. Niemann.
Proc VMV 2002 [pdf]
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[11] Microcalcification Detection using a Kernel Bayes Classifier.
B. Caputo, E. La Torre, G. E. Gigante.
Proc ISDMA 2002 [pdf]
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[10] Combining Color and Shape Information for Appearance\--based
Object Recognition
using Ultrametric Spin Glass\--Markov Random Fields.
B. Caputo, G. Dorko, H. Niemann.
Proc of Support Vector Machines Workshop, ICPR 2002 [pdf]
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[9] Toward a Quantitative Analysis of Skin Lesion Images.
B. Caputo, V. Panichelli, G. E. Gigante.
Proc MIE 2002 [doc]
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[8] A New Kernel Method for Microcalcification Detection: Spin
Glass-Markov Random Fields.
B. Caputo, E. La Torre, S. Bouattour, G. E. Gigante.
Proc MIE 2002 [doc]
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[7] Storage Capacity of Kernel Associative Memories.
B. Caputo
Proc ICANN 2002 [pdf]
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[6] To Each According to its Need: Kernel Class Specific Classifier.
B. Caputo, H. Niemann.
Proc ICPR 2002 [pdf]
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[5] Robust appearance-based Object Recognition using a
Fully Connected Markov Random Field.
B. Caputo, S. Bouattour, H. Niemann.
Proc ICPR 2002 [pdf]
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[4] A novel probabilistic model for 3D object recognition:
Spin Glass-Markov Random Fields.
B. Caputo, S. Bouattour, D. Paulus.
Proc VMV 2001 [pdf]
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[3] Digital Mammography: Gabor Filter for Detection of
Microcalcifications.
B. Caputo, G. E. Gigante.
Proc VMV 2000 [pdf]
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[2] Analysis of Periapical Lesion Using Statistical
Textural Features.
B. Caputo, G. E. Gigante.
In Proc MIE 2000
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[1] A hierarchical representation for texture classification.
B. Caputo, A. Troncone, D. Vitulano.
Proc VMV 1999 [pdf]
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