2010 Fiscal Year Final Research Report
A study on image representation by hierarchical probabilistic models and its applications
Project/Area Number |
20500129
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Intelligent informatics
|
Research Institution | Shinshu University |
Principal Investigator |
MARUYAMA Minoru Shinshu University, 工学部, 准教授 (80283232)
|
Project Period (FY) |
2008 – 2010
|
Keywords | 画像認識 / 確率的トピックモデル / パターン識別 / 識別関数 / pLSA |
Research Abstract |
We have mainly studied about hierarchical probabilistic model for image representation ant its application to category recognition. In our method, we used probabilistic topic model. We proposed a method for classifying regions in a document image based on pLSA (probabilistic latent semantic analysis). Classification is carried out based on topic proportion of the region that is estimated via MAP-based EM algorithm. The model is further extended to classify smaller image regions. We also presented the method to detect characters in a natural scene images by using decision stumps. A part of this research work received best paper award honorable mention at the IAPR workshop on Document Analysis Systems 2008.
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Research Products
(6 results)