Fast matching of large point sets under occlusions

The problem of isometric point-pattern matching can be modeled as inference in small tree-width graphical models whose embeddings in the plane are said to be ‘globally rigid’. Although such graphical models lead to efficient and exact solutions, they cannot generally handle occlusions, as even a single missing point may ‘break’ the rigidity of the graph in question. In addition, such models can efficiently handle point sets of only moderate size. In this paper, we propose a new graphical model that is not only adapted to handle occlusions but is much faster than previous approaches for solving the isometric point-pattern matching problem. We can match point-patterns with thousands of points in a few seconds. ► We introduce a new graphical model for near-isometric point-pattern matching. ► We extend methods based on global rigidity to handle occlusions. ► Previous models cannot handle occlusions, as they ‘break’ the rigidity results. ► Our method is faster and uses less memory than previous approaches. ► This allows our method to be run on much larger graphs than previous approaches.