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    • 2. 发明申请
    • HIERARCHICAL OPTIMIZATION METHOD AND SYSTEM FOR PATTERN RECOGNITION AND EDGE DETECTION
    • 用于模式识别和边缘检测的分层优化方法和系统
    • WO2006005077A2
    • 2006-01-12
    • PCT/US2005/023913
    • 2005-06-30
    • CASADEI, Stefano
    • CASADEI, Stefano
    • G06K9/68
    • G06K9/6206G06K9/6282G06T7/12G06T2207/20016G06T2207/20164
    • A method and a system for pattern recognition utilizes an ensemble of reference patterns to represent the possible instances of the models to be recognized; constructs a hierarchy of estimators to simplify and enhance the recognition of the models of interest; approximates complex reference patterns with linear compositions of simpler patterns; fragments complex patterns into local patterns so that interference between the local patterns is sufficiently small for linearization methods to be applicable; constructs estimators during an offline stage to offload calculations from the online signal processing stage; designs model estimators based on optimization principles to enhance performance and to provide performance metrics for the the estimated model instances; generates a hierarchy of reference descriptors during the offline stage, which are used for the design and construction of the model estimators. Specific examples are provided for the recognition of image features such as edges and junctions.
    • 用于模式识别的方法和系统利用参考模式的集合来表示待识别的模型的可能实例; 构建估计器的层次结构以简化和增强对感兴趣模型的识别; 使用简单模式的线性组合逼近复杂的参考模式; 将复杂图案分解成局部图案,使得局部图案之间的干扰足够小以使线性化方法可适用; 在离线阶段构建估计器以从在线信号处理阶段卸载计算; 基于优化原则设计模型估计器以提高性能并为估计的模型实例提供性能度量; 在离线阶段生成参考描述符的层次结构,用于设计和构建模型估计器。 为识别图像特征(如边缘和连接点)提供了具体示例。
    • 3. 发明申请
    • HIERARCHICAL OPTIMIZATION METHOD AND SYSTEM FOR PATTERN RECOGNITION AND EDGE DETECTION
    • 用于模式识别和边缘检测的分层优化方法和系统
    • WO2006005077B1
    • 2006-07-13
    • PCT/US2005023913
    • 2005-06-30
    • CASADEI STEFANO
    • CASADEI STEFANO
    • G06K9/68
    • G06K9/6206G06K9/6282G06T7/12G06T2207/20016G06T2207/20164
    • A method and a system for pattern recognition utilizes an ensemble of reference patterns to represent the possible instances of the models to be recognized; constructs a hierarchy of estimators to simplify and enhance the recognition of the models of interest; approximates complex reference patterns with linear compositions of simpler patterns; fragments complex patterns into local patterns so that interference between the local patterns is sufficiently small for linearization methods to be applicable; constructs estimators during an offline stage to offload calculations from the online signal processing stage; designs model estimators based on optimization principles to enhance performance and to provide performance metrics for the the estimated model instances; generates a hierarchy of reference descriptors during the offline stage, which are used for the design and construction of the model estimators. Specific examples are provided for the recognition of image features such as edges and junctions.
    • 用于模式识别的方法和系统利用参考模式的集合来表示要识别的模型的可能实例; 构建估计器的层次结构,以简化和增强感兴趣的模型的识别; 用简单图案的线性组合近似复杂参考图; 将复杂模式分段为局部模式,使得局部模式之间的干扰足够小,以使线性化方法适用; 在离线阶段构建估计器,以从在线信号处理阶段卸载计算; 基于优化原则设计模型估计器,以提高性能并为估计的模型实例提供性能指标; 在离线阶段生成参考描述符的层次结构,用于模型估计的设计和构建。 提供了用于识别诸如边缘和结的图像特征的具体示例。
    • 6. 发明申请
    • HIERARCHICAL OPTIMIZATION METHOD AND SYSTEM FOR PATTERN RECOGNITION AND EDGE DETECTION
    • 用于模式识别和边缘检测的分层优化方法和系统
    • WO2006005077A3
    • 2006-06-01
    • PCT/US2005023913
    • 2005-06-30
    • CASADEI STEFANO
    • CASADEI STEFANO
    • G06K9/68
    • G06K9/6206G06K9/6282G06T7/12G06T2207/20016G06T2207/20164
    • A method and a system for pattern recognition utilizes an ensemble of reference patterns to represent the possible instances of the models to be recognized; constructs a hierarchy of estimators to simplify and enhance the recognition of the models of interest; approximates complex reference patterns with linear compositions of simpler patterns; fragments complex patterns into local patterns so that interference between the local patterns is sufficiently small for linearization methods to be applicable; constructs estimators during an offline stage to offload calculations from the online signal processing stage; designs model estimators based on optimization principles to enhance performance and to provide performance metrics for the the estimated model instances; generates a hierarchy of reference descriptors during the offline stage, which are used for the design and construction of the model estimators. Specific examples are provided for the recognition of image features such as edges and junctions.
    • 用于模式识别的方法和系统利用参考模式的集合来表示待识别的模型的可能实例; 构建估计器的层次结构以简化和增强对感兴趣模型的识别; 使用简单模式的线性组合逼近复杂的参考模式; 将复杂图案分解成局部图案,使得局部图案之间的干扰足够小以使线性化方法可适用; 在离线阶段构建估计器以从在线信号处理阶段卸载计算; 基于优化原则设计模型估计器以提高性能并为估计的模型实例提供性能度量; 在离线阶段生成参考描述符的层次结构,用于设计和构建模型估计器。 提供了特定的例子来识别图像特征,例如边缘和连接点。