Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features-Reference-Cited by-同舟云学术

Hierarchical Support Vector Random Fields: Joint Training to Combine Local and Global Features

Published:2008 Issue: Volume: Page:527-540
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Schnitzspan Paul,Fritz Mario,Schiele Bernt

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-540-88688-4_39

Reference28 articles.

1. Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. In: CVPR (2005)

2. Felzenszwalb, P.F., Huttenlocher, D.P.: Pictorial Structures for Object Recognition. IJCV (2005)

3. Fergus, R., Zisserman, A., Perona, P.: Object class recognition by unsupervised scale invariant learning. In: CVPR 2003 (2003)

4. Leibe, B., Seemann, E., Schiele, B.: Pedestrian Detection in Crowded Scenes. In: CVPR (2005)

5. Lafferty, J., McCallum, A., Pereira, F.: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. In: ICML (2001)

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