Detecting Symmetry in Grey Level Images: The Global Optimization Approach
International Journal of Computer Vision
Towards Segmentation from Multiple Cues: Symmetry and Color
Proceedings of the 10th International Workshop on Theoretical Foundations of Computer Vision: Multi-Image Analysis
Symmetry Maps of Free-Form Curve Segments via Wave Propagation
International Journal of Computer Vision - Special Issue on Computational Vision at Brown University
A planar-reflective symmetry transform for 3D shapes
ACM SIGGRAPH 2006 Papers
Skeleton Search: Category-Specific Object Recognition and Segmentation Using a Skeletal Shape Model
International Journal of Computer Vision
Symmetry-guided texture synthesis and manipulation
ACM Transactions on Graphics (TOG)
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We present a machine vision system in which segmentation is computed in conjunction with a structural description of objects in the scene. It is assumed that contrast edges capture all relevant object information. The principles which dictate how edge features are grouped to infer objects are based upon detecting SYMMETRICAL ENCLOSING edge configurations. These are detected using ANNULAR OPERATORS applied at multiple scales to edge data which have been extracted at multiple scales from a gray level image. The subsequent grouping of symmetry points results in a set of PARTS which make it possible to identify the LOCATION of objects within an image. These parts are used as a basis for constructing coarse graph-based DESCRIPTORS for the PERCEPTUALLY SIGNIFICANT objects found in the scene. Results are presented to illustrate the method's performance on several images.