Method and system for semantic perception editing of objects in three-dimensional scene

Abstract

A method for semantic perception editing of objects in a three-dimensional scene includes steps as follows: input point cloud data of a three-dimensional scene is analyzed by using a three-dimensional instance segmentation network, and a current position and a bounding box of a target object are determined based on an editing instruction. A set of semantic relationship rules between the multiple object instances from a historical editing case database is learned by using a Bayesian dynamic updating mechanism, and dynamic semantic constraints are dynamically generated. Editing operations are converted into a standardized mathematical representation by using a unified parametric framework, and the verified editing operations are optimized based on a comprehensive loss minimizing function to obtain optimized editing parameters. The three-dimensional scene is transformed based on the optimized editing parameters to obtain the edited three-dimensional scene.