How to Use SIFT Vectors to Analyze an Image with Database Templates

During last years, local image descriptors have received much attention because of their efficiency for several computer vision tasks such as image retrieval, image comparison, features matching for 3d reconstruction... Recent surveys have shown that Scale Invariant Features Transform (SIFT) vectors are the most efficient for several criteria. In this article, we use these descriptors to analyze how a large input image is formed by small template images contained in a database. Affine transformations from database images onto the input image are found as described in [16]. We introduce a filtering step to ensure that found images do not overlap themselves when warped on the input image. A typical new application is to retrieve which products are proposed on a supermarket shelf. This is achieved using only a large picture of the shelf and a database of all products available in the supermarket. Because the database can be large and the analyze should ideally be done in a few seconds, w...

• Type: Conference
• Year: 2007
• Where: AMR
• Authors: Adrien Auclair, Laurent D. Cohen, Nicole Vincent
• Keywords: AMR 2007, Images, Input Image, Local Image Descriptors, Multimedia