Object-based Image Retrieval with Attention Analysis and Spatial Re-ranking

In this paper, a new method is proposed for object-based image retrieval. The user supplies a query object by selecting a region from a query image, and the system returns a ranked list of images that contain the same object, retrieved from a large image database. The main outcomes of this research are as follows: (1) An novel objectbased image retrieval framework that integrates effective pretreatment and re-ranking is presented, (2) a new feature filtration method based on attention analysis is proposed for pre-treatment, (3) to further improve object retrieval precision, we add an efficient spatial configuration model to re-rank the primary retrieval result using Bag of Word method. Experimental results demonstrate the effectiveness of our method.