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    • 1. 发明授权
    • Exemplar-based heterogeneous compositional method for object classification
    • 用于对象分类的基于示例的异构组合方法
    • US08233704B2
    • 2012-07-31
    • US12136138
    • 2008-06-10
    • Feng HanHui ChengJiangjian XiaoHarpreet Singh Sawhney
    • Feng HanHui ChengJiangjian XiaoHarpreet Singh Sawhney
    • G06K9/62G06E1/00G06E3/00G06F15/18G06G7/00
    • G06K9/3241G06K9/6256G06K9/6292
    • 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.
    • 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。
    • 2. 发明申请
    • EXEMPLAR-BASED HETEROGENEOUS COMPOSITIONAL METHOD FOR OBJECT CLASSIFICATION
    • 用于对象分类的基于EXEMPLAR的异构组合方法
    • US20080310737A1
    • 2008-12-18
    • US12136138
    • 2008-06-10
    • Feng HanHui ChengJiangjian XiaoHarpreet Singh Sawhney
    • Feng HanHui ChengJiangjian XiaoHarpreet Singh Sawhney
    • G06K9/62
    • G06K9/3241G06K9/6256G06K9/6292
    • 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.
    • 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。
    • 8. 发明授权
    • System and method for multi-agent event detection and recognition
    • 多代理事件检测和识别的系统和方法
    • US09569531B2
    • 2017-02-14
    • US12489667
    • 2009-06-23
    • Hui ChengChangjiang YanHarpreet Singh SawhneyFeng Han
    • Hui ChengChangjiang YanHarpreet Singh SawhneyFeng Han
    • G06F17/30G06K9/00G06K9/46G06K9/62
    • G06F17/30781G06K9/00771G06K9/4642G06K9/6292
    • 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.
    • 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。