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    • 1. 发明申请
    • OBJECT DETECTION SYSTEM BASED ON A POOL OF ADAPTIVE FEATURES
    • 基于自适应特征的对象检测系统
    • US20120121170A1
    • 2012-05-17
    • US13353485
    • 2012-01-19
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • G06K9/62
    • G06K9/6228
    • A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.
    • 公开了一种用于检测图像中的对象的存在的方法,系统和计算机程序产品。 根据实施例,用于检测图像中的对象的存在的方法包括:接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征,与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。
    • 3. 发明申请
    • OBJECT DETECTION SYSTEM BASED ON A POOL OF ADAPTIVE FEATURES
    • 基于自适应特征的对象检测系统
    • US20080232681A1
    • 2008-09-25
    • US11688372
    • 2007-03-20
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • G06K9/62
    • G06K9/6228
    • A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.
    • 公开了一种用于检测图像中的对象的存在的方法,系统和计算机程序产品。 根据实施例,用于检测图像中的对象的存在的方法包括:接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征,与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。
    • 5. 发明授权
    • Object detection system based on a pool of adaptive features
    • 基于自适应特征池的对象检测系统
    • US08655018B2
    • 2014-02-18
    • US13353485
    • 2012-01-19
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • G06K9/00
    • G06K9/6228
    • A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.
    • 公开了一种用于检测图像中的对象的存在的方法,系统和计算机程序产品。 根据实施例,用于检测图像中的对象的存在的方法包括:接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征,与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。
    • 6. 发明授权
    • Object detection system based on a pool of adaptive features
    • 基于自适应特征池的对象检测系统
    • US08170276B2
    • 2012-05-01
    • US11688372
    • 2007-03-20
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • Rogerio S. FerisArun HampapurYing-Li Tian
    • G06K9/00
    • G06K9/6228
    • A method, system and computer program product for detecting presence of an object in an image are disclosed. According to an embodiment, a method for detecting a presence of an object in an image comprises: receiving multiple training image samples; determining a set of adaptive features for each training image sample, the set of adaptive features matching the local structure of each training image sample; integrating the sets of adaptive features of the multiple training image samples to generate an adaptive feature pool; determining a general feature based on the adaptive feature pool; and examining the image using a classifier determined based on the general feature to detect the presence of the object.
    • 公开了一种用于检测图像中的对象的存在的方法,系统和计算机程序产品。 根据实施例,用于检测图像中的对象的存在的方法包括:接收多个训练图像样本; 确定每个训练图像样本的一组自适应特征,与每个训练图像样本的局部结构匹配的一组自适应特征; 整合多个训练图像样本的自适应特征的集合以生成自适应特征池; 基于自适应特征池确定一般特征; 以及使用基于一般特征确定的分类器来检查图像以检测对象的存在。
    • 7. 发明申请
    • Multispectral Detection of Personal Attributes for Video Surveillance
    • 用于视频监控的个人属性的多光谱检测
    • US20120027249A1
    • 2012-02-02
    • US12845121
    • 2010-07-28
    • Lisa M. BrownRogerio S. FerisArun HampapurDaniel A. Vaquero
    • Lisa M. BrownRogerio S. FerisArun HampapurDaniel A. Vaquero
    • G06K9/00
    • G06K9/00624G06K9/00771G06K9/2018G06K9/4614G06K9/6256
    • Techniques for detecting an attribute in video surveillance include generating training sets of multispectral images, generating a group of multispectral box features comprising receiving input of a detector size of a width and height, a number of spectral bands in the multispectral images, and integer values representing a minimum and maximum width and height of multispectral box features, fixing a feature width and to height, generating feature building blocks with the fixed width and height, placing a feature building block at a same location for each spectral band level, and enumerating combinations of the feature building blocks through each spectral level until all sizes within the integer values have been covered, and wherein each combination determines a multispectral box feature, using the training sets to select multispectral box features to generate a multispectral attribute detector, and using the multispectral attribute detector to identify a location of an attribute in video surveillance.
    • 用于检测视频监控中的属性的技术包括生成多光谱图像的训练集,生成一组多光谱特征,包括接收宽度和高度的检测器大小的输入,多光谱图像中的光谱带的数量,以及表示 多光谱盒特征的最小和最大宽度和高度,固定特征宽度和高度,生成具有固定宽度和高度的特征构建块,将特征构建块放置在每个光谱带级的相同位置,并列举 特征构成块通过每个光谱级别直到整数值中的所有尺寸已经被覆盖,并且其中每个组合确定多光谱特征,使用训练集来选择多光谱特征以产生多光谱属性检测器,并且使用多光谱属性 检测器,以识别vi中属性的位置 deo监视。