Laser point cloud scene similarity evaluation method

The invention relates to a laser point cloud scene similarity evaluation method, which comprises the following steps of: A1, respectively carrying out semantic segmentation, instance segmentation, node feature coding and node feature aggregation on two frames of laser point cloud scene data Pi and Pj which need to be subjected to similarity evaluation to obtain graph features Ei and Ej of the two frames of laser point cloud scene data; A2, calculating a similarity vector for the graph features Ei and Ej by using a pre-trained neural tensor network V, carrying out dimensionality reduction on the similarity vector through a pre-trained full connection layer to obtain a similarity score Y of the graph features Ei and Ej, and evaluating the similarity of the graph features Ei and Ej according to the similarity score Y. The laser point cloud scene similarity evaluation method has the advantages that the method is more robust and stable for scene changes such as shielding and rotation, the calculation method is sim