Symmetry detection via contour grouping

This paper presents a simple but effective model for detecting the symmetric axes of bilaterally symmetric objects in unsegmented natural scene images. Our model constructs a directed graph of symmetry interaction. Every node in the graph represents a matched pair of features, and every directed edge represents the interaction between nodes. The bilateral symmetry detection problem is then formulated as finding the star subgraph with maximal weight. The star structure ensures the consistency between grouped nodes while the optimal star subgraph can be found in polynomial time. Our model makes prediction based on contour cue: each node in the graph represents a pair of edge segments. Compared with the Loy and Eklundh's method which used SIFT feature, our model can often produce better results for the images containing limited texture. This advantage is demonstrated on two natural scene image sets.