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    • 1. 发明授权
    • Image region filling by exemplar-based inpainting
    • 图像区域填充通过基于示例的修复
    • US07551181B2
    • 2009-06-23
    • US11095138
    • 2005-03-30
    • Antonio CriminisiPatrick PerezKentaro ToyamaMichel GangnetAndrew Blake
    • Antonio CriminisiPatrick PerezKentaro ToyamaMichel GangnetAndrew Blake
    • G09G5/00
    • G06T11/001G06T11/40
    • An example-based filling system identifies appropriate filling material to replace a destination region in an image and fills the destination region using this material, thereby alleviating or minimizing the amount of manual editing required to fill a destination region in image. Tiles of image data are borrowed from the proximity of the destination region or some other source to generate new image data to fill in the region. Destination regions may be designated by user input (e.g., selection of an image region by a user) or by other means (e.g., specification of a color or feature to be replaced). In addition, the order in which the destination region is filled by example tiles may be configured to emphasize the continuity of linear structures and composite textures using a type of isophote-driven image-sampling process.
    • 基于示例的填充系统识别适当的填充材料以替换图像中的目的地区域并使用该材料填充目的地区域,从而减少或最小化填充图像中的目的地区域所需的手动编辑量。 从目的地区域或某些其他源的附近借用图像数据块以生成新的图像数据以填充该区域。 目的地区域可以由用户输入(例如,用户选择图像区域)或通过其他方式(例如,要更换的颜色或特征的指定)来指定。 此外,通过示例瓦片填充目的地区域的顺序可以被配置为使用一种类型的等轴驱动图像采样处理来强调线性结构和复合纹理的连续性。
    • 4. 发明申请
    • Probabilistic exemplar-based pattern tracking
    • 基于概率模式的模式跟踪
    • US20060093188A1
    • 2006-05-04
    • US11298798
    • 2005-12-09
    • Andrew BlakeKentaro Toyama
    • Andrew BlakeKentaro Toyama
    • G06K9/00G06K9/62
    • G06K9/6255G06K2009/3291G06T7/277
    • The present invention involves a new system and method for probabilistic exemplar-based tracking of patterns or objects. Tracking is accomplished by first extracting a set of exemplars from training data. The exemplars are then clustered using conventional statistical techniques. Such clustering techniques include k-medoids clustering which is based on a distance function for determining the distance or similarity between the exemplars. A dimensionality for each exemplar cluster is then estimated and used for generating a probabilistic likelihood function for each exemplar cluster. Any of a number of conventional tracking algorithms is then used in combination with the exemplars and the probabilistic likelihood functions for tracking patterns or objects in a sequence of images, or in a space, or frequency domain.
    • 本发明涉及一种用于模式或对象的概率示例性跟踪的新系统和方法。 通过首先从训练数据提取一组样本来实现跟踪。 然后使用常规统计技术将样本聚类。 这种聚类技术包括基于用于确定样本之间的距离或相似性的距离函数的k-聚类聚类。 然后估计每个样本簇的维数,并用于为每个样本簇生成概率似然函数。 然后将许多常规跟踪算法中的任何一种与用于跟踪图像序列中的图案或物体的样本和概率似然函数组合使用,或者在空间或频域中使用。