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公开(公告)号：US20170153116A1
公开(公告)日：2017-06-01
申请号：US15390000
申请日：2016-12-23
Inventor： Hui HUANG , Zhuming HAO , Minglun GONG , Daniel LISCHINSKI , Daniel COHEN-OR
CPC classification number: G01C21/3602 , G01C21/3638 , G06T7/0002 , G06T7/60 , G06T7/80 , G06T17/05 , G06T19/003 , G06T2200/04 , G06T2207/10028 , G06T2207/30184 , G06T2207/30241 , G06T2207/30244
Abstract: The present disclosure provides a navigation method based on a three-dimensional scene, comprising: calculating an interest value of a viewpoint of a camera based on heights, volumes, irregularities and uniqueness of buildings in a scene; generating trajectory parameters of the camera according to the interest value of the viewpoint, so as to navigate according to the trajectory parameters. The navigation method based on a three-dimensional scene of the present disclosure obtains a reasonable interest value of the viewpoint based on heights, volumes, irregularities and uniqueness of the buildings, thereby achieving a high-quality navigation.
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2.发明申请公开(公告)号：US20170193692A1
公开(公告)日：2017-07-06
申请号：US15389959
申请日：2016-12-23
Inventor： Hui HUANG , Shihao WU , Minglun GONG , Matthias ZWICKER , Daniel COHEN-OR
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.
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Patent Agency Ranking
公开(公告)号：US20170109465A1
公开(公告)日：2017-04-20
申请号：US15392688
申请日：2016-12-28
Inventor： Bin WANG , Hui HUANG , Longhua WU
CPC classification number: G06F17/5018 , G06F17/11 , G06F17/16 , G06F2217/16 , G06T13/00
Abstract: The present disclosure discloses a method and a device for elastic object deformation modeling. The method comprises: acquiring a static point cloud of the elastic object and dynamic point cloud sequences; establishing a simulation tetrahedral mesh model; driving the simulation tetrahedral mesh model to track the dynamic point cloud sequences, to obtain track deformation sequences; iteratively estimating material property coefficients and corresponding reference shapes of the elastic object; performing the following operations in each iteration: obtaining a reference shape corresponding to a current material property coefficient; driving the simulation tetrahedral mesh model to simulate the deformation from the same initial deformation according to the coefficient and the reference shape to obtain a simulation deformation sequences; calculating a positional deviation between the simulation deformation sequences and the track deformation sequences; and updating the material property coefficients in a direction in which the positional deviation is decreased; establishing an elastic object deformation model according to a material property coefficient under a minimum positional deviation and corresponding reference shape. The technical solution can establish a vivid elastic object deformation model.
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4.发明申请公开(公告)号：US20160125226A1
公开(公告)日：2016-05-05
申请号：US14893035
申请日：2013-11-26
Inventor： Hui HUANG
CPC classification number: G06K9/00214 , G06K9/00201 , G06K9/209 , G06K9/40 , G06K9/56 , G06K9/6207 , G06K9/6211 , G06K9/6249 , G06T5/002 , G06T15/10 , G06T19/00 , G06T19/20 , G06T2207/10028 , G06T2210/56
Abstract: Disclosed is a method for automatically optimizing point cloud data quality, including the following steps of: acquiring initial point cloud data for a target to be reconstructed, to obtain an initial discrete point cloud; performing preliminary data cleaning on the obtained initial discrete point cloud to obtain a Locally Optimal Projection operator (LOP) sampling model; obtaining a Possion reconstruction point cloud model by using a Possion surface reconstruction method on the obtained initial discrete point cloud; performing iterative closest point algorithm registration on the obtained Possion reconstruction point cloud model and the obtained initial discrete point cloud; and for each point on a currently registered model, calculating a weight of a surrounding point within a certain radius distance region of a position corresponding to the point for the point on the obtained LOP sampling model, and comparing the weight with a threshold, to determine whether a region where the point is located requires repeated scanning. Further disclosed is a system for automatically optimizing point cloud data quality.
Abstract translation: 公开了一种自动优化点云数据质量的方法，包括以下步骤：获取要重建的目标的初始点云数据，以获得初始离散点云; 对获得的初始离散点云执行初步数据清理，以获得本地最优投影算子（LOP）采样模型; 通过在获得的初始离散点云上使用权重表面重建方法获得权重重点云模型; 对获得的电位重建点云模型和获得的初始离散点云进行迭代最近点算法注册; 并且对于当前注册的模型中的每个点，计算与所获取的LOP采样模型上的点的点对应的位置的某个半径距离区域内的周围点的权重，并将权重与阈值进行比较，以确定 该点所在的区域是否需要重复扫描。 进一步公开了一种用于自动优化点云数据质量的系统。
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公开(公告)号：US20150363906A1
公开(公告)日：2015-12-17
申请号：US14765447
申请日：2013-09-13
Inventor： Hui HUANG , Kangxue Yin , Minglun Gong , Baoquan Chen , Yunhai Wang
CPC classification number: G06T3/0081 , G06T7/33 , G06T2207/20021
Abstract: Provided are an image restoration method and device. The method comprises: processing image blocks, which are initially registered, to acquire connection curves among the image blocks; constructing an ambient field of images to be restored by means of the connection curve; by minimizing energy of the connection curve in the ambient field, registering the image blocks; and performing image filling on the registered image blocks to acquire a restored image. The device comprises: a processing unit used for processing the image blocks, which are initially registered, to acquire the connection curve among the image blocks; an ambient field construction unit used for constructing the ambient field of the image to be restored by means of the connection curve; a registering unit used for registering the image blocks by minimizing the energy of the connection curve in the ambient field; and a filling unit used for performing image filling on the registered image blocks to acquire the restored image. The present invention can be applied to restore any damaged image and improve the accuracy.
Abstract translation: 提供了一种图像恢复方法和装置。 该方法包括：处理最初登录的图像块，以获取图像块之间的连接曲线; 通过连接曲线构建要恢复的图像的环境场; 通过最小化环境场中的连接曲线的能量，登记图像块; 并对所登记的图像块执行图像填充以获得恢复的图像。 该装置包括：用于处理最初登记的图像块的处理单元，用于获取图像块中的连接曲线; 用于通过连接曲线构造要恢复的图像的环境场的环境场结构单元; 登记单元，用于通过使环境场中的连接曲线的能量最小化来登记图像块; 以及填充单元，用于对登记的图像块执行图像填充以获取恢复的图像。 本发明可以应用于恢复任何损坏的图像并提高精度。
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公开(公告)号：US20160189005A1
公开(公告)日：2016-06-30
申请号：US14902332
申请日：2013-12-04
Inventor： Kangxue YIN , Hui HUANG
CPC classification number: G06K9/6251 , G06K9/342 , G06K9/4671 , G06K9/48 , G06K9/481 , G06K9/6207 , G06K2009/366 , G06K2009/484 , G06T7/13
Abstract: Provided is a method for extracting an image salient curve. The method comprises the following steps: drawing an approximate curve along a salient edge of an image from which a salient curve is to be extracted; obtaining short edges in the image; calculating a harmonic vector field by using the drawn curve as a boundary condition; filtering the short edges in the image by using the harmonic vector field; updating the vector field by using the short edges left in the image as boundary conditions; and obtaining an optimal salient curve of the image by using the energy of a minimized spline curve in the vector field. Also provided is a system for extracting an image salient curve. The image salient curve can ensure the smoothness and a bending characteristic.
Abstract translation: 提供一种用于提取图像突出曲线的方法。 该方法包括以下步骤：沿着要提取显着曲线的图像的显着边缘绘制近似曲线; 获得图像中的短边; 通过使用绘制曲线作为边界条件来计算谐波矢量场; 通过使用谐波矢量场对图像中的短边进行滤波; 通过使用图像中剩余的短边作为边界条件来更新矢量场; 并通过使用矢量场中最小化样条曲线的能量来获得图像的最佳显着曲线。 还提供了用于提取图像突出曲线的系统。 图像突出曲线可以确保平滑度和弯曲特性。
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公开(公告)号：US20160203636A1
公开(公告)日：2016-07-14
申请号：US14378976
申请日：2013-09-13
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 XΣi∈IΣ∈;;;;;;;;;;;;;;; （X）其中R（X）=Σi∈IγΣΣΣas as;;;;;;;;;;;;;;;;;;;;;;;; （x i - x i'）＆sgr; 我;;;; （r）= - 4r 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。
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