Generic image classification using visual knowledge on the web
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Learning Object Categories from Google"s Image Search
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Probabilistic web image gathering
Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval
Image collector III: a web image-gathering system with bag-of-keypoints
Proceedings of the 16th international conference on World Wide Web
Modeling Semantic Aspects for Cross-Media Image Indexing
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We propose a new method to select relevant images to the given keywords from images gathered from theWeb 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 shows that the results by the proposed method is almost equivalent to or outperforms 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.