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    • 1. 发明授权
    • Using a model tree of group tokens to identify an object in an image
    • 使用组令牌的模型树来标识图像中的对象
    • US08676733B2
    • 2014-03-18
    • US12692475
    • 2010-01-22
    • Bernd HeiseleYoav Sharon
    • Bernd HeiseleYoav Sharon
    • G06F15/18G06N3/00G06N3/12
    • G06K9/6219
    • Object recognition techniques are disclosed that provide both accuracy and speed. One embodiment of the present invention is an identification system. The system is capable of locating objects in images by searching for local features of an object. The system can operate in real-time. The system is trained from a set of images of an object or objects. The system computes interest points in the training images, and then extracts local image features (tokens) around these interest points. The set of tokens from the training images is then used to build a hierarchical model structure. During identification/detection, the system computes interest points from incoming target images. The system matches tokens around these interest points with the tokens in the hierarchical model. Each successfully matched image token votes for an object hypothesis at a certain scale, location, and orientation in the target image. Object hypotheses that receive insufficient votes are rejected.
    • 公开了提供精度和速度的对象识别技术。 本发明的一个实施例是识别系统。 该系统能够通过搜索对象的本地特征来定位图像中的对象。 该系统可以实时运行。 该系统是从一组对象或对象的图像中进行训练的。 系统计算训练图像中的兴趣点,然后提取这些兴趣点周围的局部图像特征(令牌)。 然后将来自训练图像的一组令牌用于构建分层模型结构。 在识别/检测期间,系统计算来自目标图像的兴趣点。 系统将这些兴趣点周围的令牌与层次模型中的令牌进行匹配。 每个成功匹配的图像标记以目标图像中的一定的尺度,位置和方向投票对象假设。 获得不足票数的对象假设被拒绝。
    • 4. 发明申请
    • USING A MODEL TREE OF GROUP TOKENS TO IDENTIFY AN OBJECT IN AN IMAGE
    • 使用组合模型树来识别图像中的对象
    • US20100121794A1
    • 2010-05-13
    • US12692475
    • 2010-01-22
    • Bernd HeiseleYoav Sharon
    • Bernd HeiseleYoav Sharon
    • G06N7/00
    • G06K9/6219
    • Object recognition techniques are disclosed that provide both accuracy and speed. One embodiment of the present invention is an identification system. The system is capable of locating objects in images by searching for local features of an object. The system can operate in real-time. The system is trained from a set of images of an object or objects. The system computes interest points in the training images, and then extracts local image features (tokens) around these interest points. The set of tokens from the training images is then used to build a hierarchical model structure. During identification/detection, the system computes interest points from incoming target images. The system matches tokens around these interest points with the tokens in the hierarchical model. Each successfully matched image token votes for an object hypothesis at a certain scale, location, and orientation in the target image. Object hypotheses that receive insufficient votes are rejected.
    • 公开了提供精度和速度的对象识别技术。 本发明的一个实施例是识别系统。 该系统能够通过搜索对象的本地特征来定位图像中的对象。 该系统可以实时运行。 该系统是从一组对象或对象的图像中进行训练的。 系统计算训练图像中的兴趣点,然后提取这些兴趣点周围的局部图像特征(令牌)。 然后将来自训练图像的一组令牌用于构建分层模型结构。 在识别/检测期间,系统计算来自目标图像的兴趣点。 系统将这些兴趣点周围的令牌与层次模型中的令牌进行匹配。 每个成功匹配的图像标记以目标图像中的一定的尺度,位置和方向投票对象假设。 获得不足票数的对象假设被拒绝。