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Block-Seminar "Machine Learning for Computer Vision"

Language

English

Termine und Informationen

Themen

Das Blockseminar wird Artikel der Machine Learning Methoden fuer die Aufgaben in Computer Vision besprechen.

• image representations including higher-order features and attributes
• object and scene categorization
• object detection and localization
• image segmentation
• large margin classifiers including multiple kernel learning
• conditional random fields and topic models
• learning (with) taxonomies
• active learning and user feedback

Literatur und Links

object and scene categorization

G. Csurka, C. Bray, C. Dance, and L. Fan, “Visual categorization with bags of keypoints,”in Workshop on Statistical Learning in Computer Vision, ECCV, Prague, Czech Republic, May 2004, pp. 1–22.
http://www.cs.utexas.edu/~grauman/courses/spring2007/395T/papers/csurka_dance_bags_keypoints.pdf
Betreuer:

S. Lazebnik, C. Schmid, and J. Ponce, “Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories,” in IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2, New York, USA, June 2006, pp. 2169–2178.
http://people.cs.ubc.ca/~lowe/525/lazebnik06.pdf
Betreuer:

M. Varma and D. Ray, “Learning the discriminative power-invariance trade-off,” in Proceedings of the IEEE 11th International Conference on Computer Vision (ICCV ’07), 2007, pp. 1–8.
http://dx.doi.org/10.1109/ICCV.2007.4408875
Betreuer:

P. Gehler and S. Nowozin, "On Feature Combination for Multiclass Object Classification", ICCV 2009.
ftp://ftp.vision.ee.ethz.ch/publications/proceedings/eth_biwi_00649.pdf
Betreuer:

image representations including higher-order features and attributes

object detection and localization

P. Viola and M. Jones, "Rapid Object Detection using a Boosted Cascade of Simple Features", 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'01), vol.1, pp. 511, 2001.

Betreuer:

M. B. Blaschko and C. H. Lampert, "Learning to Localize Objects with Structured Output Regression", Computer Vision: ECCV 2008, 2-15.
http://www.kyb.mpg.de/publications/attachments/ECCV2008-Blaschko_5247%5B0%5D.pdf
Betreuer:

image segmentation

J. Shi and J. Malik, "Normalized Cuts and Image Segmentation", IEEE Transactions on Pattern Analysis and Machine Intel ligence, 22(8):888–905, August 2000.
http://people.csail.mit.edu/torralba/courses/6.870/papers/shi00.pdf
Betreuer:

large margin classifiers including multiple kernel learning

G. R. G. Lanckriet, N. Cristianini, P. Bartlett, L. El Ghaoui, and M. I. Jordan, "Learning the kernel matrix with semidefinite programming", JMLR, 5:27–72, 2004.

Betreuer:

multi-instance?

multi-task/transfer?

conditional random fields and topic models

Ren?

Bosch?

Blei?

learning (with) taxonomies

active learning and user feedback

other topics

Derek Hoiem, Alexei A. Efros, Martial Hebert, "Putting Objects in Perspective", Int J Comput Vis (2008) 80: 3–15.
http://www.cs.cmu.edu/~efros/hoiem_ijcv2008.pdf
Betreuer:

Ng, depth?