Efficient Implementation of the Fuzzy c-Means Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM Computing Surveys (CSUR)
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Communications of the ACM
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
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Proceedings of the 6th ACM international conference on Image and video retrieval
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Proceedings of the international workshop on Workshop on multimedia information retrieval
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ACM Computing Surveys (CSUR)
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Information Retrieval
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MM '08 Proceedings of the 16th ACM international conference on Multimedia
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ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Real-time bag of words, approximately
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Content based image retrieval using visual-words distribution entropy
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Robust image retrieval using bag of visual words with fuzzy codebooks and fuzzy assignment
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Visual information retrieval systems have gained importance due to the increasing amount of available digital multimedia data. Local features employing a bag of words approach from text retrieval have outperformed global features and have enhanced retrieval performance in large data sets. In this paper we conduct an exploratory study revisiting the bag of visual words approach for content based image retrieval. We apply a fuzzy clustering technique for visual words creation and visual words assignment and show in a first attempt that fuzzy clustering leads to more robust results in terms of retrieval performance.