Automatic web image selection with a probabilistic latent topic model

We propose a new method to select relevant images to the given keywords from images gathered from the Web based on the Probabilistic Latent Semantic Analysis (PLSA) model which is a probabilistic latent topic model originally proposed for text document analysis. The experimental results show that the results by the proposed method are almost equivalent to or outperform the results by existing methods. In addition, it is proved that our method can select more various images compared to the existing SVM-based methods. Categories and Subject Descriptors: I.4 [Image Processing and Computer Vision]: Miscellaneous General Terms: Algorithms, Experimentation

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Keiji Yanai
• Keywords: Internet Technology, Latent Semantic Analysis, Probabilistic Latent Topic, Text Document Analysis, WWW 2008