Intra-class key feature weighting method for vocabulary tree based image retrieval
With the existing feature weighting methods of image retrieval field, it was impossible to use the fact that images have different key features depending on their classes because the same weight is applied to every image class. We propose a method of indexing features of each class in order of importance and giving them relevant weights, which can be applied to image retrieval. We designed a simple weight mapping function in order to enhance the distinctiveness between the image classes and also proposed a method to re-rank sub-class image set to apply different weight vectors to image retrieval framework. We demonstrated the proposed method on the existing image retrieval framework to compare and verify the performance. Proposed method was evaluated with UKBench Dataset and the result showed a noticeable improvement.