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    Non-Parametric Measurement of Media Fingerprint Weak Bits
    9.
    发明申请
    Non-Parametric Measurement of Media Fingerprint Weak Bits 有权
    媒体指纹弱位的非参数测量

    公开(公告)号：US20120011128A1

    公开(公告)日：2012-01-12

    申请号：US13173462

    申请日：2011-06-30

    申请人： Junfeng He ,  Regunathan Radhakrishnan ,  Wenyu Jiang

    发明人： Junfeng He ,  Regunathan Radhakrishnan ,  Wenyu Jiang

    IPC分类号： G06F17/30

    CPC分类号： G06F17/30023

    摘要： A value is computed for a feature in an instance of query content and compared to a threshold value. Based on the comparison, first and second bits in a hash value, which is derived from the query content feature, are determined. Conditional probability values are computed for the likelihood that quantized values of the first and the second bits equal corresponding quantized bit values of a target or reference feature value. The conditional probabilities are compared and a relative strength determined for the first and second bits, which directly corresponds to the conditional probability. The bit with the lowest bit strength is selected as the weakbit. The value of the weakbit is toggled to generate a variation of the query hash value. The query may be extended using the query hash value variation.

    摘要翻译： 为查询内容的实例中的要素计算一个值，并与阈值进行比较。 基于比较，确定从查询内容特征导出的哈希值中的第一和第二比特。 对于第一和第二比特的量化值等于目标或参考特征值的相应量化比特值的可能性，计算条件概率值。 比较条件概率，并确定第一和第二位的相对强度，其直接对应于条件概率。 选择具有最低位强度的位作为弱位。 切换弱点的值以生成查询哈希值的变体。 可以使用查询哈希值变化来扩展查询。

    PROJECTION BASED HASHING THAT BALANCES ROBUSTNESS AND SENSITIVITY OF MEDIA FINGERPRINTS
    10.
    发明申请
    PROJECTION BASED HASHING THAT BALANCES ROBUSTNESS AND SENSITIVITY OF MEDIA FINGERPRINTS 失效
    基于投影的平衡消除平衡媒体指纹的鲁棒性和灵敏度

    公开(公告)号：US20110299721A1

    公开(公告)日：2011-12-08

    申请号：US13115542

    申请日：2011-05-25

    申请人： Junfeng He ,  Regunathan Radhakrishnan ,  Claus Bauer

    发明人： Junfeng He ,  Regunathan Radhakrishnan ,  Claus Bauer

    IPC分类号： G06K9/00

    CPC分类号： G06K9/00744 ,  G06K9/6232

    摘要： Multiple candidate feature components of media content or projection matrices (or other hash functions, e.g., non-linear projections) are identified. Each of the candidate projection matrices (or other hash functions) includes an array of coefficients that relate to the candidate features. A subgroup of the candidate features or the projection matrices (or other hash functions) are selected based at least partially on an optimized combination of at least two characteristics of the candidate features or projection matrices (or other hash functions). Media fingerprints that uniquely identify the media content are derived from the selected optimized subgroup. Optimal projection matrices (or other hash functions) may be designed. Performance or sensitivity (e.g., search time) characteristics of the fingerprints are thus balanced with robustness characteristics thereof.

    摘要翻译： 识别媒体内容或投影矩阵（或其他散列函数，例如非线性投影）的多个候选特征分量。 每个候选投影矩阵（或其他散列函数）包括与候选特征相关的系数阵列。 至少部分地基于候选特征或投影矩阵（或其他散列函数）的至少两个特征的优化组合来选择候选特征或投影矩阵（或其他散列函数）的子组。 唯一标识媒体内容的媒体指纹是从选定的优化子组派生出来的。 可以设计最佳投影矩阵（或其他散列函数）。 因此，指纹的性能或灵敏度（例如，搜索时间）特性与其鲁棒性特性相平衡。