Graph Theoretical Approach To Detection Of Outliers In Point Clouds
Point clouds can be seen as the graphs that vertices are embedded in Euclidean space. In this paper, we present a
heuristic outlier detection method by using graph theoretical concepts. This method is less dependent to noise in the raw
point cloud data and efficient in to capture geometric properties by defining edges of the graph via threshold distances.