Relevance feedback has been shown to be an effective tool to enhance content-based information retrieval (CBIR) systems. We propose a new approach to relevance feedback by warping the database's feature space, or shifting the objects' data points in a controlled manner responding to user feedback. We demonstrate that given consistent feedback, the performance of the retrieval system can be significantly increased.