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  Learning Smooth Pooling Regions for Visual Recognition

Malinowski, M., & Fritz, M. (2013). Learning Smooth Pooling Regions for Visual Recognition. In T. Burghardt, D. Damen, W. Mayol-Cuevas, & M. Mirmehdi (Eds.), Electronic Proceedings of the British Machine Vision Conference 2013 (pp. 1-11). Durham: BMVA Press. doi:10.5244/C.27.118.

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 Creators:
Malinowski, Mateusz1, Author           
Fritz, Mario1, Author           
Affiliations:
1Computer Vision and Multimodal Computing, MPI for Informatics, Max Planck Society, ou_1116547              

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 Abstract: From the early HMAX model to Spatial Pyramid Matching, spatial pooling has played an important role in visual recognition pipelines. By aggregating local statistics, it equips the recognition pipelines with a certain degree of robustness to translation and deformation yet preserving spatial information. Despite of its predominance in current recognition systems, we have seen little progress to fully adapt the pooling strategy to the task at hand. In this paper, we propose a flexible parameterization of the spatial pooling step and learn the pooling regions together with the classifier. We investigate a smoothness regularization term that in conjuncture with an efficient learning scheme makes learning scalable. Our framework can work with both popular pooling operators: sum-pooling and max-pooling. Finally, we show benefits of our approach for object recognition tasks based on visual words and higher level event recognition tasks based on object-bank features. In both cases, we improve over the hand-crafted spatial pooling step showing the importance of its adaptation to the task.

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Language(s): eng - English
 Dates: 2013
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 757
DOI: 10.5244/C.27.118
 Degree: -

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Title: 24th British Machine Vision Conference
Place of Event: Bristol, UK
Start-/End Date: 2013-09-09 - 2013-09-13

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Title: Electronic Proceedings of the British Machine Vision Conference 2013
  Abbreviation : BMVC 2013
Source Genre: Proceedings
 Creator(s):
Burghardt, Tilo1, Editor
Damen, Dima1, Editor
Mayol-Cuevas, Walterio1, Editor
Mirmehdi, Majid1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Durham : BMVA Press
Pages: - Volume / Issue: - Sequence Number: 118 Start / End Page: 1 - 11 Identifier: -