1. A method comprising: extracting a feature vector from each image of a set of images; receiving a query image; determining a plurality of classification boundaries in feature space by determining a classification boundary for each feature based on the query image and the extracted feature vectors; providing, via a processor, a first set of images determined to be relevant with respect to the query image, responsive to a determination of a proximity of the extracted image features being with the respective classification boundaries; providing, via a processor, a second set of images in which each image of the second set of images is selected due to having a first feature of the extracted feature vector of an image determined to be relevant with respect to the query image and a second feature of the extracted feature vector of the image determined to be irrelevant with respect to the query image, responsive to a determination of the first feature being within the classification boundary associated with the first feature and the second feature being outside the classification boundary associated with the second feature; receiving relevance feedback with respect to at least one image of the second set of images, the relevance feedback indicating a degree to which the at least one image of the second set of images is relevant to the query image; updating the classification boundaries in response to the relevance feedback; and providing updates to the first set of images and the second set of images, responsive to a determination of a proximity of image features to the updated classification boundaries.