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Correlated PLSA for Image Clustering

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Advances in Multimedia Modeling (MMM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6523))

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Abstract

Probabilistic Latent Semantic Analysis (PLSA) has become a popular topic model for image clustering. However, the traditional PLSA method considers each image (document) independently, which would often be conflict with the real occasion. In this paper, we presents an improved PLSA model, named Correlated Probabilistic Latent Semantic Analysis (C-PLSA). Different from PLSA, the topics of the given image are modeled by the images that are related to it. In our method, each image is represented by bag-of-visual-words. With this representation, we calculate the cosine similarity between each pair of images to capture their correlations. Then we use our C-PLSA model to generate K latent topics and Expectation Maximization (EM) algorithm is utilized for parameter estimation. Based on the latent topics, image clustering is carried out according to the estimated conditional probabilities. Extensive experiments are conducted on the publicly available database. The comparison results show that our approach is superior to the traditional PLSA for image clustering.

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Author information

Authors and Affiliations

  1. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, P.R. China

    Peng Li, Jian Cheng, Zechao Li & Hanqing Lu

  2. China-Singapore Institute of Digital Media, Singapore, 119613, Singapore

    Peng Li, Jian Cheng, Zechao Li & Hanqing Lu

Authors
  1. Peng Li
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  2. Jian Cheng
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  3. Zechao Li
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  4. Hanqing Lu
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Editor information

Editors and Affiliations

  1. National Taiwan Ocean University, Keelung, Taiwan

    Kuo-Tien Lee  & Jun-Wei Hsieh  & 

  2. National Chiao Tung University, Hsinchu, Taiwan

    Wen-Hsiang Tsai

  3. Academia Sinica, Taipei, Taiwan

    Hong-Yuan Mark Liao

  4. Cornell University, Ithaca, NY, USA

    Tsuhan Chen

  5. National Kaohsiung First University of Science and Technology, Kaohsiung, Taiwan

    Chien-Cheng Tseng

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© 2011 Springer-Verlag Berlin Heidelberg

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Li, P., Cheng, J., Li, Z., Lu, H. (2011). Correlated PLSA for Image Clustering. In: Lee, KT., Tsai, WH., Liao, HY.M., Chen, T., Hsieh, JW., Tseng, CC. (eds) Advances in Multimedia Modeling. MMM 2011. Lecture Notes in Computer Science, vol 6523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17832-0_29

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  • DOI: https://doi.org/10.1007/978-3-642-17832-0_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17831-3

  • Online ISBN: 978-3-642-17832-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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