公开(公告)号：US20170193692A1

公开(公告)日：2017-07-06

申请号：US15389959

申请日：2016-12-23

Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES

Inventor： Hui HUANG ,  Shihao WU ,  Minglun GONG ,  Matthias ZWICKER ,  Daniel COHEN-OR

IPC: G06T17/00 ,  G06T7/60 ,  G06T7/20 ,  G06T5/00

CPC classification number: G06T17/00 ,  G06T5/002 ,  G06T7/20 ,  G06T7/60 ,  G06T13/40 ,  G06T2207/10028 ,  G06T2210/56

Abstract: The present disclosure provides a three-dimensional point cloud model reconstruction method, a computer readable storage medium and a device. The method comprises: 1) sampling and WLOP-consolidating an input point set to generate an initial surface point set, copying the initial surface point set as an initial position of an interior skeleton point set, to establish a correspondence relation between surface points and skeleton points; 2) moving points in the interior skeleton point set inwards along a direction opposite to a normal vector thereof, to generate interior points; 3) using a self-adaptive anisotropic neighborhood as a regularization term to perform an optimization of the interior points, and generating skeleton points; 4) performing a consolidation and completion of the initial surface point set using the skeleton points, to generate consolidated surface points; 5) reconstructing a three-dimensional point cloud model according to the skeleton points, the surface points and the correspondence relation between the surface points and the skeleton points.

公开(公告)号：US20160203636A1

公开(公告)日：2016-07-14

申请号：US14378976

申请日：2013-09-13

Applicant: SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY CHINESE ACADEMY OF SCIENCES

Inventor： Hui HUANG ,  Shihao WU ,  Baoquan CHEN ,  Liangliang NAN

IPC: G06T17/00

CPC classification number: G06T17/00 ,  G06T2210/56

Abstract: A method for extracting a skeleton form a point cloud includes: obtaining inputted point cloud sampling data; contracting the point cloud using an iterative formula and obtaining skeleton branches, the iterative formula is: argmin X  ∑ i ∈ I   ∑ j ∈ J    x i - q i   θ  (  x j - q j  ) + R  ( X ) ,  wherein R  ( X ) = ∑ i ∈ I   γ i  ∑ i ′ ∈ I  \  { i }   θ  (  x i - x i ′  ) σ i   x i - x i ′  , θ  ( r ) =  - 4   r 2 h 2 , wherein J represents a point set of the point cloud sampling data, q represents the sampling points in the point set J, I represents a neighborhood point set of the sampling points q, x represents the neighborhood points in the neighborhood point set I, R is a regular term, γ is a weighting coefficient, h is a neighborhood radius of the neighborhood point set I, and σ is a distribution coefficient; and connecting the skeleton branches and obtaining a point cloud skeleton.

Abstract translation: 一种用于从点云提取骨架的方法包括：获得输入的点云采样数据; 使用迭代公式收集点云并获得骨架分支，迭代公式为：argmin XΣi∈IΣ∈;;;;;;;;;;;;;;; （X）其中R（X）=Σi∈IγΣΣΣas as;;;;;;;;;;;;;;;;;;;;;;;; （x i - x i'）＆sgr; 我;;;; （r）= - 4r 2 h 2，其中J表示点云采样数据的点集，q表示点集合J中的采样点，I表示采样点q的邻域点集 ，x表示邻域点集I中的邻域，R是常规项，γ是加权系数，h是邻域点集I的邻域半径，＆sgr; 是分布系数; 并连接骨架分支并获得点云骨架。