利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

54 条记录 (耗时 0.036 秒)

    Method and apparatus for inferring the geographic location of captured scene depictions
    3.
    发明授权
    Method and apparatus for inferring the geographic location of captured scene depictions 有权
    用于推断拍摄场景描述的地理位置的方法和装置

    公开(公告)号：US08989483B2

    公开(公告)日：2015-03-24

    申请号：US13493654

    申请日：2012-06-11

    申请人： Hui Cheng ,  Harpreet Singh Sawhney ,  Bogdan Calin Mihai Matei ,  Zhiwei Zhu ,  Nicholas John Vander Valk

    发明人： Hui Cheng ,  Harpreet Singh Sawhney ,  Bogdan Calin Mihai Matei ,  Zhiwei Zhu ,  Nicholas John Vander Valk

    IPC分类号： G06K9/00

    CPC分类号： G06K9/00671

    摘要： A method and apparatus for determining a geographic location of a scene in a captured depiction comprising extracting a first set of features from the captured depiction by algorithmically analyzing the captured depiction, matching the extracted features of the captured depiction against a second set of extracted features associated with reference depictions with known geographic locations and when the matching is successful, identifying the geographic location of the scene in the captured depiction based on a known geographic location of a matching reference depiction from the reference depictions.

    摘要翻译： 一种用于确定拍摄描述中的场景的地理位置的方法和装置，包括通过对所捕获的描绘进行算法分析来提取所捕获的描述中的第一组特征，将所提取的描绘的特征与所提取的特征相关联的第二组进行匹配 具有已知地理位置的参考描述，并且当匹配成功时，基于来自参考描述的匹配参考描述的已知地理位置来识别所捕获的描绘中场景的地理位置。

    Real-time action detection and classification
    4.
    发明授权
    Real-time action detection and classification 有权
    实时动作检测与分类

    公开(公告)号：US08634638B2

    公开(公告)日：2014-01-21

    申请号：US12488911

    申请日：2009-06-22

    申请人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney ,  Sang-Hack Jung ,  Rakesh Kumar ,  Yanlin Guo

    发明人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney ,  Sang-Hack Jung ,  Rakesh Kumar ,  Yanlin Guo

    IPC分类号： G06K9/62

    CPC分类号： G06K9/00342

    摘要： The present invention relates to a method and system for creating a strong classifier based on motion patterns wherein the strong classifier may be used to determine an action being performed by a body in motion. When creating the strong classifier, action classification is performed by measuring similarities between features within motion patterns. Embodiments of the present invention may utilize candidate part-based action sets and training samples to train one or more weak classifiers that are then used to create a strong classifier.

    摘要翻译： 本发明涉及一种用于基于运动模式创建强分类器的方法和系统，其中强分类器可用于确定由运动中的身体执行的动作。 当创建强分类器时，通过测量运动模式中的特征之间的相似度来执行动作分类。 本发明的实施例可以利用基于候选部分的动作集和训练样本来训练一个或多个弱分类器，然后将其用于创建强分类器。

    Real-Time Action Detection and Classification
    5.
    发明申请
    Real-Time Action Detection and Classification 有权
    实时行动检测与分类

    公开(公告)号：US20090316983A1

    公开(公告)日：2009-12-24

    申请号：US12488911

    申请日：2009-06-22

    申请人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney ,  Sang-Hack Jung ,  Rakesh Kumar ,  Yanlin Guo

    发明人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney ,  Sang-Hack Jung ,  Rakesh Kumar ,  Yanlin Guo

    IPC分类号： G06K9/62

    CPC分类号： G06K9/00342

    摘要： The present invention relates to a method and system for creating a strong classifier based on motion patterns wherein the strong classifier may be used to determine an action being performed by a body in motion. When creating the strong classifier, action classification is performed by measuring similarities between features within motion patterns. Embodiments of the present invention may utilize candidate part-based action sets and training samples to train one or more weak classifiers that are then used to create a strong classifier.

    摘要翻译： 本发明涉及一种用于基于运动模式创建强分类器的方法和系统，其中强分类器可用于确定由运动中的身体执行的动作。 当创建强分类器时，通过测量运动模式中的特征之间的相似度来执行动作分类。 本发明的实施例可以利用基于候选部分的动作集和训练样本来训练一个或多个弱分类器，然后将其用于创建强分类器。

    Method and apparatus for correlating and viewing disparate data
    6.
    发明授权
    Method and apparatus for correlating and viewing disparate data 有权
    用于关联和查看不同数据的方法和装置

    公开(公告)号：US09053194B2

    公开(公告)日：2015-06-09

    申请号：US13484520

    申请日：2012-05-31

    申请人： Harpreet Singh Sawhney ,  Jayakrishnan Eledath ,  Ajay Divakaran ,  Mayank Bansal ,  Hui Cheng

    发明人： Harpreet Singh Sawhney ,  Jayakrishnan Eledath ,  Ajay Divakaran ,  Mayank Bansal ,  Hui Cheng

    IPC分类号： G06F17/30

    CPC分类号： G06F17/2785 ,  G06F17/30047 ,  G06F17/30867 ,  G06F17/3087

    摘要： A computer-implemented method comprising collecting data from a plurality of information sources, identifying a geographic location associated with the data and forming a corresponding event according to the geographic location, correlating the data and the event with one or more topics based at least partly on the identified geographic location and storing the correlated data and event and inferring the associated geographic location if the data does not comprise explicit location information, including matching the data against a database of geo-referenced data.

    摘要翻译： 一种计算机实现的方法，包括从多个信息源收集数据，识别与所述数据相关联的地理位置并根据所述地理位置形成对应的事件，至少部分地基于所述数据和所述事件与一个或多个主题相关联 所识别的地理位置并存储相关数据和事件，并且如果数据不包括显式位置信息，则推断相关联的地理位置，包括将数据与地理参考数据的数据库进行匹配。

    Exemplar-based heterogeneous compositional method for object classification
    7.
    发明授权
    Exemplar-based heterogeneous compositional method for object classification 有权
    用于对象分类的基于示例的异构组合方法

    公开(公告)号：US08233704B2

    公开(公告)日：2012-07-31

    申请号：US12136138

    申请日：2008-06-10

    申请人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney

    发明人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney

    IPC分类号： G06K9/62 ,  G06E1/00 ,  G06E3/00 ,  G06F15/18 ,  G06G7/00

    CPC分类号： G06K9/3241 ,  G06K9/6256 ,  G06K9/6292

    摘要： A method for automatically generating a strong classifier for determining whether at least one object is detected in at least one image is disclosed, comprising the steps of: (a) receiving a data set of training images having positive images; (b) randomly selecting a subset of positive images from the training images to create a set of candidate exemplars, wherein said positive images include at least one object of the same type as the object to be detected; (c) training a weak classifier based on at least one of the candidate exemplars, said training being based on at least one comparison of a plurality of heterogeneous compositional features located in the at least one image and corresponding heterogeneous compositional features in the one of set of candidate exemplars; (d) repeating steps (c) for each of the remaining candidate exemplars; and (e) combining the individual classifiers into a strong classifier, wherein the strong classifier is configured to determine the presence or absence in an image of the object to be detected.

    摘要翻译： 公开了一种用于自动生成强分类器以确定在至少一个图像中是否检测到至少一个对象的方法，包括以下步骤：（a）接收具有正图像的训练图像的数据集; （b）从所述训练图像中随机选择正图像的子集以创建一组候选样本，其中所述正图像包括与所述待检测对象相同类型的至少一个对象; （c）基于所述候选样本中的至少一个来训练弱分类器，所述训练基于位于所述至少一个图像中的多个异质成分特征和所述一个图像中的一个中的对应的异质组成特征的至少一个比较 候选人样本 （d）为每个其余的候选样本重复步骤（c）; 以及（e）将各个分类器组合成强分类器，其中强分类器被配置为确定待检测对象的图像中的存在或不存在。

    EXEMPLAR-BASED HETEROGENEOUS COMPOSITIONAL METHOD FOR OBJECT CLASSIFICATION
    8.
    发明申请
    EXEMPLAR-BASED HETEROGENEOUS COMPOSITIONAL METHOD FOR OBJECT CLASSIFICATION 有权
    用于对象分类的基于EXEMPLAR的异构组合方法

    公开(公告)号：US20080310737A1

    公开(公告)日：2008-12-18

    申请号：US12136138

    申请日：2008-06-10

    申请人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney

    发明人： Feng Han ,  Hui Cheng ,  Jiangjian Xiao ,  Harpreet Singh Sawhney

    IPC分类号： G06K9/62

    CPC分类号： G06K9/3241 ,  G06K9/6256 ,  G06K9/6292

    摘要： A method for automatically generating a strong classifier for determining whether at least one object is detected in at least one image is disclosed, comprising the steps of: (a) receiving a data set of training images having positive images; (b) randomly selecting a subset of positive images from the training images to create a set of candidate exemplars, wherein said positive images include at least one object of the same type as the object to be detected; (c) training a weak classifier based on at least one of the candidate exemplars, said training being based on at least one comparison of a plurality of heterogeneous compositional features located in the at least one image and corresponding heterogeneous compositional features in the one of set of candidate exemplars; (d) repeating steps (c) for each of the remaining candidate exemplars; and (e) combining the individual classifiers into a strong classifier, wherein the strong classifier is configured to determine the presence or absence in an image of the object to be detected.

    摘要翻译： 公开了一种用于自动生成强分类器以确定在至少一个图像中是否检测到至少一个对象的方法，包括以下步骤：（a）接收具有正图像的训练图像的数据集; （b）从所述训练图像中随机选择正图像的子集以创建一组候选样本，其中所述正图像包括与所述待检测对象相同类型的至少一个对象; （c）基于所述候选样本中的至少一个训练弱分类器，所述训练基于位于所述至少一个图像中的多个异质成分特征和所述一个图像中的一个中的对应的异质组成特征的至少一个比较 候选人样本 （d）为每个其余的候选样本重复步骤（c）; 以及（e）将各个分类器组合成强分类器，其中强分类器被配置为确定待检测对象的图像中的存在或不存在。

    System and method for multi-agent event detection and recognition
    9.
    发明授权
    System and method for multi-agent event detection and recognition 有权
    多代理事件检测和识别的系统和方法

    公开(公告)号：US09569531B2

    公开(公告)日：2017-02-14

    申请号：US12489667

    申请日：2009-06-23

    申请人： Hui Cheng ,  Changjiang Yan ,  Harpreet Singh Sawhney ,  Feng Han

    发明人： Hui Cheng ,  Changjiang Yan ,  Harpreet Singh Sawhney ,  Feng Han

    IPC分类号： G06F17/30 ,  G06K9/00 ,  G06K9/46 ,  G06K9/62

    CPC分类号： G06F17/30781 ,  G06K9/00771 ,  G06K9/4642 ,  G06K9/6292

    摘要： A method and system for creating a histogram of oriented occurrences (HO2) is disclosed. A plurality of entities in at least one image are detected and tracked. One of the plurality of entities is designated as a reference entity. A local 2-dimensional ground plane coordinate system centered on and oriented with respect to the reference entity is defined. The 2-dimensional ground plane is partitioned into a plurality of non-overlapping bins, the bins forming a histogram, a bin tracking a number of occurrences of an entity class. An occurrence of at least one other entity of the plurality of entities located in the at least one image may be associated with one of the plurality of non-overlapping bins. A number of occurrences of entities of at least one entity class in at least one bin may be into a vector to define an HO2 feature.

    摘要翻译： 公开了一种用于创建定向事件直方图（HO2）的方法和系统。 检测并跟踪至少一个图像中的多个实体。 多个实体之一被指定为参照实体。 定义以参考实体为中心并定向的局部二维地面坐标系。 二维接地平面被划分成多个不重叠的箱体，该箱体形成一个直方图，一个箱子跟踪一个实体类的出现次数。 位于所述至少一个图像中的所述多个实体中的至少一个其他实体的出现可以与所述多个非重叠区域中的一个相关联。 在至少一个箱中的至少一个实体类的实体的多个出现可以被转换为向量以定义HO2特征。

    Method and apparatus for detecting and tracking vehicles
    10.
    发明授权
    Method and apparatus for detecting and tracking vehicles 有权
    用于车辆检测和跟踪的方法和装置

    公开(公告)号：US08712096B2

    公开(公告)日：2014-04-29

    申请号：US13041092

    申请日：2011-03-04

    申请人： Jiangjian Xiao ,  Harpreet Singh Sawhney ,  Hui Cheng

    发明人： Jiangjian Xiao ,  Harpreet Singh Sawhney ,  Hui Cheng

    IPC分类号： G06K9/00

    CPC分类号： G06K9/6296 ,  G06K9/00624 ,  G06T7/254

    摘要： The present invention relates to a method and apparatus for detecting and tracking vehicles. One embodiment of a system for detecting and tracking an object (e.g., vehicle) in a field of view includes a moving object indication stage for detecting a candidate object in a series of input video frames depicting the field of view and a track association stage that uses a joint probabilistic graph matching framework to associate an existing track with the candidate object.

    摘要翻译： 本发明涉及车辆检测跟踪方法和装置。 用于在视野中检测和跟踪对象（例如，车辆）的系统的一个实施例包括用于检测描绘视场的一系列输入视频帧中的候选对象的移动对象指示级和跟踪关联级， 使用联合概率图匹配框架将现有轨道与候选对象相关联。