Multi-class object recognition by fusion of image descriptors: classification evaluation of PASCAL VOC Challenge database (パターン認識・メディア理解)

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概要

• 論文の詳細を見る

• Category recognition is important to access visual information on the level of objects. Over the past several years, substantial performance gains on challenging benchmark datasets have been reported in the literature. This progress can be attributed to two developments: the design of highly discriminative and robust image features and the combination of multiple complementary features based on different aspects such as shape, appearance. In this paper we extract different appearance descriptors for several properties of local keypionts obtained by grid sampling, Harris and Difference of Gaussian (DoG), and a shape descriptor-Pyramid Histogram of Orientation Gradient (PHOG). The extracted descriptors are evaluated by PASCAL VOC database with nonlinear SVM classifiers, and they also are combined for evaluation. The experimental results show that the accuracy rate with fusion of different image descriptors can be improved.

• 2009-11-19

著者

• Chen Yen-Wei

  College of Information and Science, Ristumeikan University

• han Xian-Hua

  College of Information Science and Engineering, Ritsumeikan University

• Ruan Xiang

  Omron Corporation

• Ruan Xiang

  Omron Corp. Kusatsu‐shi Jpn

• Han Xianhua

  Graduate School Of Science And Engineering Ritsumeikan University

• Han Xian‐hua

  Ritsumeikan Univ. Kusatsu‐shi Jpn

• Chen Yen

  College Of Information Science And Engineering Ritsumeikan University

• Han Xian-hua

  College Of Information Science And Engineering Ritsumeikan University

• Han Xian

  Faculty Of Engineering University Of The Ryukyus

• Chen Y‐w

  College Of Information Science And Engineering Ritsumeikan University

• Han Xian‐hua

  College Of Information Science And Engineering Ritsumeikan University

• Chen Yen-wei

  College Of Information And Science Ristumeikan University

• Chen Yen-wei

  College Of Information And Science Ritsumeikan University

• Han Xianhua

  College of Information Science and Engineering, Ritsumeikan University

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