A Comparative Study of Different Constraints in Random Sampling Consensus Algorithm
The RANSAC algorithm has been widely used in point cloud registration to estimate transformation parame-ters. In recent years,many researchers propose to improve registration accuracy and shorten time by adding constraints to the RANSAC algorithm. However,the effects of the con-straints and their relationships are not yet clear. This paper performs a comparison study for four constraints and combines them into sixteen combinations. In the experiments,two de-scriptors are respectively used to establish the initial correspon-dences set for point clouds,and then the RANSAC algorithm with different constraints is used to calculate the transforma-tion parameters. The registration accuracy and computational efficiency are compared. By experiments,these These combi-nations are also compared and analyzed in the experiment. The effects of different combinations are compared,and the advantages and disadvantages of different constraints are giv-en.
point cloud registrationRANSACconstraintslocal shape descriptor
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