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    DETERMINING FLUID LEAKAGE VOLUME IN PIPELINES
    1.
    发明申请
    DETERMINING FLUID LEAKAGE VOLUME IN PIPELINES 有权
    确定流体中的流体泄漏体积

    公开(公告)号：US20140229124A1

    公开(公告)日：2014-08-14

    申请号：US14128640

    申请日：2012-03-31

    申请人： Felipe Albertao ,  Ying Chen ,  Jin Huang ,  Chunhua Tian ,  Hao Wang ,  Jing Xiao

    发明人： Felipe Albertao ,  Ying Chen ,  Jin Huang ,  Chunhua Tian ,  Hao Wang ,  Jing Xiao

    IPC分类号： G01F1/34

    CPC分类号： F17D5/06 ,  F17D5/02 ,  G01F1/34 ,  G01F22/02 ,  G01M3/2815

    摘要： A method and an apparatus for determining leakage volume of fluid in transportation pipelines are provided. The method comprises: obtaining the negative pressure wave signals detected by at least two pressure sensors arranged on the pipeline; determining the pressure signal at the leakage location based on the negative pressure wave signals; determining the leakage rate during a leakage period based on the pressure signal at the leakage location according to a leakage model; and determining the leakage volume of the fluid in the pipeline based on the leakage rate and the leakage period. The apparatus provided corresponds to the method described above. By using the method and apparatus described above, the leakage volume of the transportation pipelines can be obtained to help understand the leakage profile of the pipelines and thus reduce losses.

    摘要翻译： 提供了一种用于确定运输管道中的流体泄漏体积的方法和装置。 该方法包括：获得由布置在管道上的至少两个压力传感器检测的负压波信号; 基于负压波信号确定泄漏位置处的压力信号; 根据泄漏模型，根据泄漏位置处的压力信号确定泄漏期间的泄漏率; 并基于泄漏率和泄漏周期来确定管道中流体的泄漏体积。 所提供的装置对应于上述方法。 通过使用上述方法和装置，可以获得运输管线的泄漏量，以帮助了解管道的泄漏特征，从而减少损失。

    DATA PROCESSING METHOD AND SYSTEM FOR CHECKING PIPELINE LEAKAGE
    3.
    发明申请
    DATA PROCESSING METHOD AND SYSTEM FOR CHECKING PIPELINE LEAKAGE 审中-公开
    用于检查管道泄漏的数据处理方法和系统

    公开(公告)号：US20130085690A1

    公开(公告)日：2013-04-04

    申请号：US13643665

    申请日：2011-04-21

    申请人： Ben Fei ,  Chunhua Tian ,  Dong Wang ,  Hao Wang ,  Xian Wu ,  Jing Xiao

    发明人： Ben Fei ,  Chunhua Tian ,  Dong Wang ,  Hao Wang ,  Xian Wu ,  Jing Xiao

    IPC分类号： G06F17/18

    CPC分类号： G06F17/18 ,  E21B47/10 ,  F17D1/00 ,  F17D3/01 ,  F17D5/02 ,  F17D5/06 ,  G01M3/2807 ,  G01M3/2815 ,  H04Q9/00 ,  H04Q2209/84

    摘要： A method for checking pipeline leakage comprises: receiving detecting parameters collected by at least one sensor with respect to pipelines in its corresponding region; gathering detecting parameters collected by the at least one sensor; analyzing the gathered detecting parameters to obtain an evolutionary tendency of detecting parameters in the corresponding region of the at least one sensor; judging if the evolutionary tendency of the detecting parameters satisfies predefined features of leakage; determining that pipeline leakage exists in the corresponding region if the evolutionary tendency of the detecting parameters satisfies the predefined features of leakage. The present invention may help to determine leak regions with a leakage having small flow quantity, and provide a user with regions with pipeline leakage to be detected based on a resource constraint.

    摘要翻译： 一种用于检查管道泄漏的方法，包括：接收由至少一个传感器相对于其对应区域中的管线收集的检测参数; 收集由所述至少一个传感器收集的检测参数; 分析所收集的检测参数以获得在所述至少一个传感器的相应区域中检测参数的进化趋势; 判断检测参数的进化趋势是否满足预定的泄漏特征; 如果检测参数的进化趋势满足预定的泄漏特征，则确定在相应区域中存在管道泄漏。 本发明可以帮助确定具有小流量的泄漏的泄漏区域，并且基于资源约束向用户提供要检测的管道泄漏的区域。

    Adaptive threshold for object detection
    5.
    发明授权
    Adaptive threshold for object detection 有权
    物体检测的自适应阈值

    公开(公告)号：US08948522B2

    公开(公告)日：2015-02-03

    申请号：US13198412

    申请日：2011-08-04

    申请人： Yuanyuan Ding ,  Jing Xiao

    发明人： Yuanyuan Ding ,  Jing Xiao

    IPC分类号： G06K9/62 ,  G06K9/46

    CPC分类号： G06K9/624 ,  G06K9/4642 ,  G06K9/6269

    摘要： Systems and methods for developing and using adaptive threshold values for different input images for object detection are disclosed. In embodiments, detector response histogram-based systems and methods train models for predicting optimal threshold values for different images. In embodiments, when training the model, an optimal threshold value for an image is defined as the value that maximizes the reduction of false positive image patches while preserving as many true positive image patches as possible. Once trained, the model may be used to set different threshold values for different images by inputting a detector response histogram for the image patches of an image into the model to determine a threshold value for detection.

    摘要翻译： 公开了用于开发和使用用于对象检测的不同输入图像的自适应阈值的系统和方法。 在实施例中，基于检测器响应直方图的系统和方法训练用于预测不同图像的最佳阈值的模型。 在实施例中，当训练模型时，图像的最佳阈值被定义为最大化假阳性图像斑块的减少的值，同时保留尽可能多的真正的正图像斑块。 一旦被训练，该模型可以用于通过将图像的图像块的检测器响应直方图输入到模型中来确定用于检测的阈值来为不同的图像设置不同的阈值。

    Multiview face content creation
    6.
    发明授权
    Multiview face content creation 有权
    Multiview面对内容创作

    公开(公告)号：US08933928B2

    公开(公告)日：2015-01-13

    申请号：US13303044

    申请日：2011-11-22

    申请人： Derek Shiell ,  Jing Xiao

    发明人： Derek Shiell ,  Jing Xiao

    IPC分类号： G06T15/00 ,  G06T17/00 ,  G06T15/20

    CPC分类号： G06T17/00 ,  G06T15/205

    摘要： New views of a 2D image are generated by identifying an object class within the image, such as through a face detector. The face is then fitted to a model face by means of an AAM, and the results extended to a fitted 3D polygon mesh face. A boundary perimeter with predefined anchor points and a predefined triangulation with the 3D polygon mesh is defined a predefined depth distance from the depth center of known landmarks within the 3D polygon mesh face. By rotating the 3D polygon mesh face relative to the boundary perimeter, which may follow the perimeter of the input image, new views of the input image are generated.

    摘要翻译： 通过识别图像内的对象类（例如通过面部检测器）来生成2D图像的新视图。 然后通过AAM将面部安装到模型面上，并将结果扩展到拟合的3D多边形网格面。 定义了与3D多边形网格预定义三角剖分的边界周界，与3D多边形网格面内的已知界标深度中心的预定深度距离。 通过旋转3D多边形网格面相对于可能跟随输入图像的周边的边界周界，生成输入图像的新视图。

    Continuous linear dynamic systems
    7.
    发明授权
    Continuous linear dynamic systems 有权
    连续线性动态系统

    公开(公告)号：US08917907B2

    公开(公告)日：2014-12-23

    申请号：US13406011

    申请日：2012-02-27

    申请人： Jinjun Wang ,  Jing Xiao

    发明人： Jinjun Wang ,  Jing Xiao

    IPC分类号： G06K9/00 ,  G06K9/62

    CPC分类号： G06K9/00765 ,  G06K9/00335 ,  G06K9/6297

    摘要： Aspects of the present invention include systems and methods for segmentation and recognition of action primitives. In embodiments, a framework, referred to as the Continuous Linear Dynamic System (CLDS), comprises two sets of Linear Dynamic System (LDS) models, one to model the dynamics of individual primitive actions and the other to model the transitions between actions. In embodiments, the inference process estimates the best decomposition of the whole sequence into continuous alternating between the two set of models, using an approximate Viterbi algorithm. In this way, both action type and action boundary may be accurately recognized.

    摘要翻译： 本发明的方面包括用于分割和识别动作原语的系统和方法。 在实施例中，被称为连续线性动态系统（CLDS）的框架包括两组线性动态系统（LDS）模型，其中一个模型用于对各个原始动作的动力学进行建模，另一组模型对动作之间的转换进行建模。 在实施例中，推理过程使用近似维特比算法来估计整个序列的最佳分解到两组模型之间的连续交替。 以这种方式，可以准确地识别动作类型和动作边界。

    Context constrained novel view interpolation
    8.
    发明授权
    Context constrained novel view interpolation 有权
    背景约束小说视图插值

    公开(公告)号：US08817071B2

    公开(公告)日：2014-08-26

    申请号：US12814920

    申请日：2010-06-14

    申请人： Xianwang Wang ,  Jing Xiao

    发明人： Xianwang Wang ,  Jing Xiao

    IPC分类号： H04N17/02 ,  G06K9/48 ,  G06K9/00

    CPC分类号： G06T15/205 ,  G06T7/90 ,  G06T7/97 ,  G06T17/00 ,  G06T2207/20228 ,  H04N13/111 ,  H04N13/243

    摘要： Aspects of the present invention include systems and methods for generating a novel view interpolation. In embodiments, feature correspondences and geometrical contexts are used to find additional correspondences based on the assumption of the local linear transformation. The accuracy and the number of correspondence matches may be improved by iterative refinement. Having obtained a set of correspondences, a novel view image can be generated.

    摘要翻译： 本发明的方面包括用于生成新颖视图插值的系统和方法。 在实施例中，使用特征对应和几何上下文来基于局部线性变换的假设来找到附加的对应关系。 可以通过迭代细化来改善对准匹配的准确性和数量。 获得了一组通信，可以生成一个新颖的视图图像。

    Identifying text pixels in scanned images
    9.
    发明授权
    Identifying text pixels in scanned images 失效
    识别扫描图像中的文本像素

    公开(公告)号：US08606010B2

    公开(公告)日：2013-12-10

    申请号：US13051223

    申请日：2011-03-18

    申请人： Jing Xiao

    发明人： Jing Xiao

    IPC分类号： G06K9/34

    CPC分类号： G06K9/6257 ,  G06K2209/01

    摘要： A processor and method make use of multiple weak classifiers to construct a single strong classifier to identify regions that contain text within an input image document. The weak classifiers are grouped by their computing cost from low to median to high, and each weak classifier is assigned a weight value based on its ability to accurately identify text regions. A level 1 classifier is constructed by selecting weak classifiers from the low group, a level 2 classifier is constructed by selecting weak classifiers from the low and median groups, and a level 3 classifier is constructed by selecting weak classifiers from the low, median and high groups. Regions that the level 1 classifier identifies as containing text are submitted to the level 2 classifier, and regions that the level 2 classifier identifies as containing text are submitted to the level 3 classifier.

    摘要翻译： 处理器和方法利用多个弱分类器来构造单个强分类器来识别包含输入图像文档内的文本的区域。 弱分类器的计算成本从低到中等到高，每个弱分类器都基于其准确识别文本区域的能力来分配权重值。 通过从低组中选择弱分类器构建1级分类器，通过从低和中值组中选择弱分类器构建2级分类器，通过从低，中，高选择弱分类器构建3级分类器 团体 1级分类器识别为包含文本的区域被提交给2级分类器，2级分类器识别为包含文本的区域被提交到3级分类器。

    Local difference pattern based local background modeling for object detection
    10.
    发明授权
    Local difference pattern based local background modeling for object detection 有权
    基于局部差异模式的本地背景建模对象检测

    公开(公告)号：US08565482B2

    公开(公告)日：2013-10-22

    申请号：US13198382

    申请日：2011-08-04

    申请人： Yuanyuan Ding ,  Jing Xiao

    发明人： Yuanyuan Ding ,  Jing Xiao

    IPC分类号： G06K9/46 ,  G06K9/62

    CPC分类号： G06K9/4671 ,  G06K9/4642 ,  G06K9/527

    摘要： Systems and methods for object detection that consider background information are presented. Embodiments of the present invention utilizing a feature called Local Difference Pattern (LDP), which is more discriminative for modeling local background image features. In embodiments, the LDP feature is used to train detection models. In embodiments, the LDP feature may be used in detection to differentiate different image background conditions and adaptively adjust classification to yield higher detection rates.

    摘要翻译： 介绍了考虑背景信息的物体检测系统和方法。 利用称为局部差异模式（LDP）的特征的本发明的实施例，其更为区分对本地背景图像特征的建模。 在实施例中，LDP特征用于训练检测模型。 在实施例中，LDP特征可以用于检测以区分不同的图像背景条件并且自适应地调整分类以产生更高的检测率。