Methods and systems for surface fitting based change detection in 3D point-cloud

A system (102) for change detection in a surface represented by 3D point-cloud, wherein the system comprises a memory (204) operatively coupled to one or more hardware processors (202) and configured to store instructions configured for execution by the one or more hardware processors (202), further the system comprises:

• a registration module (212) is configured to:
• acquire a reference point-cloud defining a reference surface and a template point-cloud defining a template surface, wherein the reference point-cloud and the template point-cloud correspond to the 3D point-cloud of the surface acquired at different time instances;
• and
• align the template surface with the reference surface by performing registration of the template point-cloud and the reference point-cloud, wherein the registration of the reference point-cloud and the template point-cloud is based on shape similarity based constraints;
• a subsampling module (214) is configured to:
• equalize point density of the registered reference point-cloud and the registered template point-cloud by performing subsampling to provide a processed reference point-cloud and a processed template point-cloud;
• a change detection module (216) configured to:
• reduce noise from the processed reference point-cloud and the processed template point-cloud by estimating a smooth reference surface and a smooth template surface using a locally weighted Moving Least Squares (MLS) approximation;
• voxelize the smooth reference surface to generate a plurality of reference voxels and the smooth template surface to generate a plurality of template voxels, wherein each reference voxel is defined by a plurality of reference vertices and each template voxel is defined by a plurality of template vertices;
• determine a corresponding reference vertex for every template vertex of each template voxel using a kd-tree, wherein the kd-tree is set with the plurality of reference vertices of a reference voxel;
• and
• determine vertex distance between every template vertex and the determined corresponding reference vertex, wherein the determined vertex distance above a predefined vertex distance threshold is indicative of the change in the surface represented by the 3D-point-cloud;
• and
• generate an output point-cloud indicating change detected in the template point-cloud with respect to the reference point-cloud.

A non-transitory computer-readable medium storing instructions, which, when executed by a hardware processor, cause the hardware processor to perform acts comprising:

• acquiring a reference point-cloud defining a reference surface and a template point-cloud defining a template surface, wherein the reference point-cloud and the template point-cloud correspond to a 3D point-cloud of a surface acquired at different time instances;
• aligning the template surface with the reference surface by performing registration of the template point-cloud and the reference point-cloud, wherein the registration of the reference point-cloud and the template point-cloud is based on shape similarity based constraints;
• equalizing point density of the registered reference point-cloud and the registered template point-cloud by performing subsampling to provide a processed reference point-cloud and a processed template point-cloud;
• reducing noise from the processed reference point-cloud and the processed template point-cloud by estimating a smooth reference surface and a smooth template surface using a locally weighted Moving Least Squares (MLS) approximation;
• voxelizing the smooth reference surface to generate a plurality of reference voxels and the smooth template surface to generate a plurality of template voxels, wherein each reference voxel is defined by a plurality of reference vertices and each template voxel is defined by a plurality of template vertices;
• determining a corresponding reference vertex for every template vertex of each template voxel using a kd-tree, wherein the kd-tree is set with the plurality of reference vertices of a reference voxel;
• and
• determining vertex distance between every template vertex and the determined corresponding reference vertex, wherein the determined vertex distance above a predefined vertex distance threshold is indicative of the change in the surface represented by the 3D-point-cloud;
• and
• generating an output point-cloud indicating change detected in the template point-cloud with respect to the reference point-cloud.