Detecting multiple symmetries with extended SIFT

This paper describes an effective method for detecting multiple symmetric objects in an image. A “pseudo-affine invariant SIFT” is used for detecting symmetric feature pairs in perspective images. Candidates of symmetric axes are estimated from every two symmetric feature pairs, and the one supported by the most symmetric feature pairs is detected as the most relevant symmetric axis of a symmetric object. The symmetric feature pairs supporting the symmetric axis are then used to detect other symmetric axes in the same symmetric object. This procedure is applied repeatedly to the symmetric feature pairs after eliminating the ones that support the already detected symmetric axes to detect all symmetric objects in the image. The effectiveness of this method has been confirmed through several experiments using real images and common image databases.