公开(公告)号：US20140226895A1

公开(公告)日：2014-08-14

申请号：US13972349

申请日：2013-08-21

Applicant: LSI Corporation

Inventor： Dmitry Nicolaevich Babin ,  Alexander Alexandrovich Petyushko ,  Ivan Leonidovich Mazurenko ,  Alexander Borisovich Kholodenko ,  Denis Vladimirovich Parkhomenko

IPC: G06K9/00

CPC classification number: G06K9/00214 ,  G06T7/33 ,  G06T2207/10028

Abstract: A method and system for registration of three-dimensional (3D) image frames is disclosed. The method includes receiving two point clouds representing two 3D image frames obtained at two time instances; locating the origins for the two point clouds; constructing two 2D grids for representing the two point clouds, wherein each 2D grid is constructed based on spherical representation of its corresponding point cloud and origin; identifying two sets of feature points based on the two 2D grids constructed; establishing a correspondence between the first set of feature points and the second set of feature points based on a neighborhood radius threshold; and determining an orthogonal transformation between the first 3D image frame and the second 3D image frame based on the correspondence between the first set of feature points and the second set of feature points.

Abstract translation: 公开了用于三维（3D）图像帧的配准的方法和系统。 该方法包括接收表示在两个时间实例获得的两个3D图像帧的两个点云; 找出两点云的起源; 构建用于表示两点云的两个2D网格，其中基于其对应的点云和原点的球面表示构建每个2D网格; 基于构建的两个2D网格识别两组特征点; 基于邻域半径阈值建立第一组特征点与第二组特征点之间的对应关系; 以及基于所述第一组特征点和所述第二组特征点之间的对应关系来确定所述第一3D图像帧与所述第二3D图像帧之间的正交变换。

公开(公告)号：US09294128B2

公开(公告)日：2016-03-22

申请号：US14027371

申请日：2013-09-16

Applicant: LSI Corporation

Inventor： Denis Vladimirovich Zaytsev ,  Ivan Leonidovich Mazurenko ,  Alexander Alexandrovich Petyushko ,  Aleksey Alexandrovich Letunovskiy ,  Pavel Aleksandrovich Aliseitchik ,  Dmitry Nicolaevich Babin

IPC: H03M13/13 ,  H03M13/11 ,  H03M13/01

CPC classification number: H03M13/1102 ,  H03M13/015 ,  H03M13/1142

Abstract: A method for estimating error rates in low-density parity check codes includes calibrating an encoder according to specific channel parameters and according to dominant error events in the low-density parity-check code. Dominant codewords are classified based on characteristics of each codeword that are likely to produce similar error rates at similar noise levels; codeword classes that produce the highest error rate are then tested. Error boundary distance is estimated using multiple binary searches on segments. Segments are defined based on codeword, trapping set and biasing noise components of the channel. To improve calculation speed the most significant subclasses of codewords, trapping sets and noise signals are used.

Abstract translation: 用于估计低密度奇偶校验码中的误码率的方法包括根据特定信道参数和根据低密度奇偶校验码中的主要误差事件来校准编码器。 主要码字基于每个码字的特征进行分类，这些特征可能在类似噪声水平下产生类似的错误率; 然后测试产生最高错误率的码字类。 使用段上的多个二进制搜索来估计误差边界距离。 基于信道的码字，陷印集和偏置噪声分量来定义分段。 为了提高计算速度，使用码字，陷阱集和噪声信号的最重要的子类。

公开(公告)号：US20140226854A1

公开(公告)日：2014-08-14

申请号：US13973040

申请日：2013-08-22

Applicant: LSI Corporation

Inventor： Ivan Leonidovich Mazurenko ,  Alexander Alexandrovich Petyushko ,  Denis Vladimirovich Parkhomenko ,  Alexander Borisovich Kholodenko ,  Dmitry Nicolaevich Babin

IPC: G06K9/00

CPC classification number: G06K9/00201 ,  G06T7/248 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/30201

Abstract: A method and system for key frame based region of interest (ROI) tracking is disclosed. The method includes storing a key ROI set in a key ROI buffer, the key ROI set including at least one key ROI; designating one of the key ROI in the key ROI set as an active key ROI; receiving a point cloud representing a particular ROI to be processed for tracking; establishing a correspondence between that particular ROI and the active key ROI; determining whether to switch the active key designation to another key ROI in the key ROI set and switching the active key designation accordingly; and determining whether to modify the key ROI set and modifying the key ROI set accordingly.

Abstract translation: 公开了一种基于关键帧的感兴趣区域（ROI）跟踪的方法和系统。 该方法包括将关键ROI集合存储在关键ROI缓冲器中，所述关键ROI集合包括至少一个关键ROI; 指定关键投资回报率作为主要投资回报率的关键ROI之一; 接收代表要进行跟踪的特定ROI的点云; 建立该特定ROI与活动密钥ROI之间的对应关系; 确定在所述关键ROI集合中是否将活动密钥指定切换到另一关键ROI，并相应地切换所述活动密钥指定; 并确定是否修改关键的ROI集合并相应地修改关键的ROI集合。

公开(公告)号：US20140245086A1

公开(公告)日：2014-08-28

申请号：US14027371

申请日：2013-09-16

Applicant: LSI Corporation

Inventor： Denis Vladimirovich Zaytsev ,  Ivan Leonidovich Mazurenko ,  Alexander Alexandrovich Petyushko ,  Aleksey Alexandrovich Letunovskiy ,  Pavel Aleksandrovich Aliseitchik ,  Dmitry Nicolaevich Babin

IPC: H03M13/13

CPC classification number: H03M13/1102 ,  H03M13/015 ,  H03M13/1142

Abstract: A method for estimating error rates in low-density parity check codes includes calibrating an encoder according to specific channel parameters and according to dominant error events in the low-density parity-check code. Dominant codewords are classified based on characteristics of each codeword that are likely to produce similar error rates at similar noise levels; codeword classes that produce the highest error rate are then tested. Error boundary distance is estimated using multiple binary searches on segments. Segments are defined based on codeword, trapping set and biasing noise components of the channel. To improve calculation speed the most significant subclasses of codewords, trapping sets and noise signals are used.

Abstract translation: 用于估计低密度奇偶校验码中的误码率的方法包括根据特定信道参数和根据低密度奇偶校验码中的主要误差事件来校准编码器。 主要码字基于每个码字的特征进行分类，这些特征可能在类似噪声水平下产生类似的错误率; 然后测试产生最高错误率的码字类。 使用段上的多个二进制搜索来估计误差边界距离。 基于信道的码字，陷印集和偏置噪声分量来定义分段。 为了提高计算速度，使用码字，陷阱集和噪声信号的最重要的子类。

公开(公告)号：US09336431B2

公开(公告)日：2016-05-10

申请号：US13973040

申请日：2013-08-22

Applicant: LSI Corporation

Inventor： Ivan Leonidovich Mazurenko ,  Alexander Alexandrovich Petyushko ,  Denis Vladimirovich Parkhomenko ,  Alexander Borisovich Kholodenko ,  Dmitry Nicolaevich Babin

IPC: G06K9/00 ,  G06T7/20

CPC classification number: G06K9/00201 ,  G06T7/248 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/30201

Abstract: A method and system for key frame based region of interest (ROI) tracking is disclosed. The method includes storing a key ROI set in a key ROI buffer, the key ROI set including at least one key ROI; designating one of the key ROI in the key ROI set as an active key ROI; receiving a point cloud representing a particular ROI to be processed for tracking; establishing a correspondence between that particular ROI and the active key ROI; determining whether to switch the active key designation to another key ROI in the key ROI set and switching the active key designation accordingly; and determining whether to modify the key ROI set and modifying the key ROI set accordingly.

Abstract translation: 公开了一种基于关键帧的感兴趣区域（ROI）跟踪的方法和系统。 该方法包括将关键ROI集合存储在关键ROI缓冲器中，所述关键ROI集合包括至少一个关键ROI; 指定关键投资回报率作为主要投资回报率的关键ROI之一; 接收代表要进行跟踪的特定ROI的点云; 建立该特定ROI与活动密钥ROI之间的对应关系; 确定在所述关键ROI集合中是否将活动密钥指定切换到另一关键ROI，并相应地切换所述活动密钥指定; 并确定是否修改关键的ROI集合并相应地修改关键的ROI集合。

公开(公告)号：US20150242681A1

公开(公告)日：2015-08-27

申请号：US14424953

申请日：2013-04-16

Applicant: LSI Corporation

Inventor： Pavel Aleksandrovich Aliseitchik ,  Denis Vladimirovich Zaytsev ,  Denis Vasilyevich Parfenov ,  Aleksey Alexandrovich Letunovskiy ,  Dmitry Nicolaevich Babin

IPC: G06K9/00 ,  G06T1/60

CPC classification number: G06K9/00335 ,  G06F3/042 ,  G06K9/00973 ,  G06K9/4604 ,  G06K2009/4666 ,  G06T1/60

Abstract: The disclosure is directed to a system and method of image processing. According to various embodiments of the disclosure, a storage module in communication with a plurality of memory banks stores a plurality of pixels of an image in the memory banks and interleaves the memory banks to enable a plurality of image scanners to access the plurality of pixels. A scanning module scans a selection of pixels in at least four directions relative to a first pixel of the plurality of pixels utilizing the plurality of image scanners. A singular points detection module in communication with the scanning module acquires a depth of each pixel of the selection of scanned pixels and determines a singularity value of the first pixel by comparing the depth of the first pixel with the depth of each pixel of the selection of pixels.

Abstract translation: 本公开涉及一种图像处理系统和方法。 根据本公开的各种实施例，与多个存储体通信的存储模块将多个像素的像素存储在存储体中，并交织存储体，以使得多个图像扫描器能够访问多个像素。 扫描模块利用多个图像扫描仪扫描相对于多个像素中的第一像素的至少四个方向的像素选择。 与扫描模块通信的奇点检测模块获取扫描像素的选择的每个像素的深度，并且通过将第一像素的深度与选择的每个像素的深度进行比较来确定第一像素的奇异值 像素。

公开(公告)号：US20140095955A1

公开(公告)日：2014-04-03

申请号：US13743381

申请日：2013-01-17

Applicant: LSI CORPORATION

Inventor： Denis Vladimirovich Zaytsev ,  Denis Vasilievich Parfenov ,  Yang Han ,  Ivan Leonidovich Mazurenko ,  Dmitry Nicolaevich Babin

IPC: H03M13/37

CPC classification number: H03M13/3738 ,  H03M13/09 ,  H03M13/1142

Abstract: A method for ordering trapping sets to find one or more dominant trapping sets includes analyzing a trapping set and a random set of codewords to generate a distance value for each trapping set, and ordering the trapping sets by the distance value. Distance values may be determined for each trapping set by tracking a vote count wherein a correct decode at a certain noise level produces a “right” vote and an incorrect decode at a certain noise level produces a “left” vote. A certain threshold number of “left” votes terminates processing at that noise level.

Abstract translation: 用于排序陷阱集合以找到一个或多个主要捕获集合的方法包括分析陷阱集合和随机的码字集合以生成每个陷阱集合的距离值，并且将陷阱集合排序距离值。 可以通过跟踪投票计数来确定每个陷阱集合的距离值，其中在某一噪声级别的正确解码产生“正确”投票，并且在某一噪声电平处产生不正确的解码产生“左”投票。 一定数量的“左”选票终止在该噪声级别的处理。

公开(公告)号：US08977925B2

公开(公告)日：2015-03-10

申请号：US13743381

申请日：2013-01-17

Applicant: LSI Corporation

Inventor： Denis Vladimirovich Zaytsev ,  Denis Vasilievich Parfenov ,  Yang Han ,  Ivan Leonidovich Mazurenko ,  Dmitry Nicolaevich Babin

IPC: H03M13/00 ,  H03M13/37 ,  H03M13/11

CPC classification number: H03M13/3738 ,  H03M13/09 ,  H03M13/1142

Abstract: A method for ordering trapping sets to find one or more dominant trapping sets includes analyzing a trapping set and a random set of codewords to generate a distance value for each trapping set, and ordering the trapping sets by the distance value. Distance values may be determined for each trapping set by tracking a vote count wherein a correct decode at a certain noise level produces a “right” vote and an incorrect decode at a certain noise level produces a “left” vote. A certain threshold number of “left” votes terminates processing at that noise level.

Abstract translation: 用于排序陷阱集合以找到一个或多个主要捕获集合的方法包括分析陷阱集合和随机的码字集合以生成每个陷阱集合的距离值，并且将陷阱集合排序距离值。 可以通过跟踪投票计数来确定每个陷阱集合的距离值，其中在某一噪声级别的正确解码产生“正确”投票，并且在某一噪声电平处产生不正确的解码产生“左”投票。 一定数量的“左”选票终止在该噪声级别的处理。