For the registration of partially overlapping point clouds, this paper
proposes an effective approach based on both the hard and soft assignments.
Given two initially posed clouds, it firstly establishes the forward
correspondence for each point in the data shape and calculates the value of
binary variable, which can indicate whether this point correspondence is
located in the overlapping areas or not. Then, it establishes the bilateral
correspondence and computes bidirectional distances for each point in the
overlapping areas. Based on the ratio of bidirectional distances, the
exponential function is selected and utilized to calculate the probability
value, which can indicate the reliability of the point correspondence.
Subsequently, both the values of hard and soft assignments are embedded into
the proposed objective function for registration of partially overlapping point
clouds and a novel variant of ICP algorithm is proposed to obtain the optimal
rigid transformation. The proposed approach can achieve good registration of
point clouds, even when their overlap percentage is low. Experimental results
tested on public data sets illustrate its superiority over previous approaches
on accuracy and robustness.