Method and system for generating 3D mesh of a scene using RGBD image sequence

    公开(公告)号:US11941760B2

    公开(公告)日:2024-03-26

    申请号:US17807339

    申请日:2022-06-16

    CPC classification number: G06T17/20 G06T7/70 G06T2207/10024

    Abstract: Traditional machine learning (ML) based systems used for scene recognition and object recognition have the disadvantage that they require huge quantity of labeled data to generate data models for the purpose of aiding the scene and object recognition. The disclosure herein generally relates to image processing, and, more particularly, to method and system for generating 3D mesh generation using planar and non-planar data. The system extracts planar point cloud and non-planar point cloud from each RGBD image in a sequence of RGBD images fetched as input, and then generates a planar mesh and a non-planar mesh for planar and non-planar objects in the image. A mesh representation is generated by merging the planar mesh and the non-planar mesh. Further, an incremental merging of the mesh representation is performed on the sequence of RGBD images, based on an estimated camera pose information, to generate representation of the scene.

    Systems and methods for shape constrained 3D point cloud registration

    公开(公告)号:US10586305B2

    公开(公告)日:2020-03-10

    申请号:US15872557

    申请日:2018-01-16

    Abstract: Systems and methods of the present disclosure facilitate rigid point cloud registration with characteristics including shape constraint, translation proportional to distance and spatial point-set distribution model for handling scale. The method of the present disclosure enables registration of a rigid template point cloud to a given reference point cloud. Shape-constrained gravitation, as induced by the reference point cloud, controls movement of the template point cloud such that at each iteration, the template point cloud better aligns with the reference point cloud in terms of shape. This enables alignment in difficult conditions introduced by change such as presence of outliers and/or missing parts, translation, rotation and scaling. Also, systems and methods of the present disclosure provide an automated method as against conventional methods that depended on manually adjusted parameters.

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