Patent ID: 7113944
Filing Date: 2006-09-26
Classification: G06F,G06K,Y10S

Abstract:
1. One or more computer-readable media having computer-executable instructions that, when executed by a computer, perform a method for improving iterative results of Content-Based Image Retrieval (CBIR) using relevance feedback, the method comprising: obtaining a set of positive feedback images and a set of negative feedback images via relevance feedback, the set of positive feedback images are those images deemed semantically relevant and the set of negative feedback images are those deemed semantically less relevant; constructing a Bayesian classifier of a positive feedback image by positive candidate images; within a feature space, moving a positive candidate image towards the set of positive feedback images by adjusting distance metrics of the positive candidate image, the positive candidate image having similar low-level features as those of the set of positive feedback images, wherein the adjusting of distance metrics of the positive candidate image employs this evaluation: where within a feature space, distancing a negative candidate image from the set of positive feedback images by adjusting distance metrics of the negative candidate image, the negative candidate image having similar low-level features as those of the set of negative feedback images.