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    • 8. 发明申请
    • SYSTEM AND METHOD FOR TRACKING AND RECOGNIZING PEOPLE
    • 跟踪和识别人的系统和方法
    • US20130136298A1
    • 2013-05-30
    • US13306783
    • 2011-11-29
    • Ting YuPeter Henry TuDashan GaoKunter Seref AkbayYi Yao
    • Ting YuPeter Henry TuDashan GaoKunter Seref AkbayYi Yao
    • G06K9/00
    • G06K9/00362G06K9/00771G06K9/6218G06K9/6232G06K9/66G06T7/70
    • A tracking and recognition system is provided. The system includes a computer vision-based identity recognition system configured to recognize one or more persons, without a priori knowledge of the respective persons, via an online discriminative learning of appearance signature models of the respective persons. The computer vision-based identity recognition system includes a memory physically encoding one or more routines, which when executed, cause the performance of constructing pairwise constraints between the unlabeled tracking samples. The computer vision-based identity recognition system also includes a processor configured to receive unlabeled tracking samples collected from one or more person trackers and to execute the routines stored in the memory via one or more algorithms to construct the pairwise constraints between the unlabeled tracking samples.
    • 提供跟踪和识别系统。 该系统包括基于计算机视觉的身份识别系统,其被配置为通过对各个人的外观签名模型的在线辨别学习来识别一个或多个人,而没有相应人员的先验知识。 基于计算机视觉的身份识别系统包括物理地对一个或多个例程进行编码的存储器,当被执行时,引起在未标记的跟踪样本之间构建成对约束的性能。 基于计算机视觉的身份识别系统还包括处理器,其被配置为接收从一个或多个人跟踪器收集的未标记的跟踪样本,并且经由一个或多个算法来执行存储在存储器中的例程,以构建未标记的跟踪样本之间的成对约束。
    • 9. 发明授权
    • Computer-implemented system and method for recognizing patterns in a digital image through document image decomposition
    • 用于通过文档图像分解识别数字图像中的图案的计算机实现的系统和方法
    • US08139865B2
    • 2012-03-20
    • US13012770
    • 2011-01-24
    • Yizhou WangDashan GaoHaitham HindiMinh Binh Do
    • Yizhou WangDashan GaoHaitham HindiMinh Binh Do
    • G06K9/66G06K9/34G06K9/62
    • G06K9/00469
    • A computer-implemented system and method for retrieving a digital image through document image decomposition is provided. A stored digital image is retrieved. Generic visual features are extracted. The features are grouped into a primitive layer including word-graphs that each include words and features. The words are grouped into a layout layer including zone hypotheses that each include one or more of the words. Causal dependencies between the word-graphs and the zone hypotheses are expressed through zone models that include a joint probability defining a pair of probabilistic models generated through a learned binary edge classifier. Each pair of probabilistic models is expressed as an optimal set selection problem including a set of cost functions and constraints. The optimal set selection problem is evaluated through a heuristic search of the cost functions and constraints and a non-overlapping optimal set of the zone hypotheses is provided that characterize the stored digital image.
    • 提供了一种用于通过文档图像分解来检索数字图像的计算机实现的系统和方法。 检索存储的数字图像。 提取一般视觉特征。 这些特征被分组成包括单词和特征的单词图形的原始图层。 这些单词被分组成一个布局层,包括区域假设,每一个都包含一个或多个单词。 通过区域模型来表达字图和区域假设之间的因果依赖关系,该区域模型包括定义通过学习的二进制边缘分类器生成的一对概率模型的联合概率。 每对概率模型被表示为包括一组成本函数和约束的最优集合选择问题。 通过对成本函数和约束的启发式搜索来评估最优集合选择问题,并且提供表征存储的数字图像的区域假设的非重叠最优集合。