A Relevance Feedback Algorithm Based on SVM Model's Dynamic Adjusting for Image Retrieval

A fixed SVM model setting is not suitable for the evolvement of the pattern of user's interest. In this paper a relevance feedback algorithm based on SVM model's dynamic adjusting for image retrieval is presented. In this algorithm, there is no need to fix the model's parameters beforehand, and the parameters of SVM model will be automatically adjusted corresponding to the changing of the training samples. Experimental results show the proposed algorithm outperformed other algorithms with fixed model's parameter.