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    • 1. 发明授权
    • Object recognition for three-dimensional bodies
    • 三维体的物体识别
    • US09424461B1
    • 2016-08-23
    • US13929672
    • 2013-06-27
    • Amazon Technologies, Inc.
    • Chang YuanGeoffrey Scott HellerOleg RybakovSharadh RamaswamyJim Oommen Thomas
    • G06K9/00
    • G06K9/00201G06K9/00208G06K9/00214
    • Various embodiments utilize two-dimensional (“2D”) and three-dimensional (“3D”) object features for purposes such as object recognition and/or image matching. For example, a user can capture an image (e.g., still images or video) of an object and can receive information about items that are determined to match the object. For example, the image can be analyzed to detect visual features (e.g., corners, edges, etc.) of the object and the detected visual features can be combined to generate a combined visual feature vector which can be used for object recognition, image matching, or other such purposes. Other approaches utilize the image to generate a 3D model of the object represented in the image, which can be used to determine at least one object or types of objects that match the object represented in the image.
    • 各种实施例利用二维(“2D”)和三维(“3D”)对象特征用于诸如对象识别和/或图像匹配的目的。 例如,用户可以捕获对象的图像(例如,静止图像或视频),并且可以接收关于被确定为匹配对象的项目的信息。 例如,可以分析图像以检测对象的视觉特征(例如,角,边等),并且可以组合检测到的视觉特征以生成可用于对象识别,图像匹配的组合视觉特征向量 ,或其他此类用途。 其他方法利用图像来生成在图像中表示的对象的3D模型,其可以用于确定与图像中表示的对象匹配的对象的至少一个对象或类型。
    • 6. 发明授权
    • Image-based character recognition
    • 基于图像的字符识别
    • US09058536B1
    • 2015-06-16
    • US13627643
    • 2012-09-26
    • Amazon Technologies, Inc.
    • Chang YuanGeoffrey Scott HellerLouis L. LeGrand, IIIDaniel Bibireata
    • G06K9/00G06K9/20
    • G06K9/2054G06K9/72G06K2209/01
    • Various embodiments enable a computing device to capture multiple images (or video) of text and provide at least a portion of the same to a recognizer to separately recognize text from each image. Each of the recognized outputs will typically include one or more text strings for each image. Substrings common to each of the one or more text strings are computed and compared to each text string within each image to determine an alignment consensus for each substring within the text. A template string is generated that includes each common substring in a position corresponding to a determined alignment for a respective substring. A character frequency vote is then applied to unresolved portions and the final text string is determined by filling the unresolved spaces with the character having the highest occurrence rate for a respective space.
    • 各种实施例使得计算设备能够捕获文本的多个图像(或视频),并将其至少一部分提供给识别器以分别识别来自每个图像的文本。 每个识别的输出通常将包括每个图像的一个或多个文本串。 对一个或多个文本串中的每一个公共的子字符串进行计算,并将其与每个图像中的每个文本字符串进行比较,以确定文本中每个子字符串的对齐一致性。 生成模板字符串,该模板字符串包括与相应子字符串的确定对齐方式对应的位置中的每个公共子字符串。 然后将字符频率投票应用于未解决的部分,并且通过用对于相应空间具有最高出现率的字符填充未解决的空间来确定最终文本串。