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    • 2. 发明授权
    • Validation and correction of map data using oblique images
    • 使用倾斜图像验证和校正地图数据
    • US08311287B2
    • 2012-11-13
    • US12237817
    • 2008-09-25
    • Pragyana K. MishraEyal OfekGur Kimchi
    • Pragyana K. MishraEyal OfekGur Kimchi
    • G06K9/00
    • G06K9/6286G06T7/0002G06T17/05G06T2207/10032
    • Technologies are described herein for validating and correcting map data using oblique images or aerial photographs taken at oblique angles to the earth's surface. Pixels within oblique images can be analyzed to detect, validate, and correct other sources of data used in generating maps such as vector data, elevation maps, projection parameters, and three-dimensional model data. Visibility and occlusion information in oblique views may be analyzed to reduce errors in either occluding or occluded entities. Occlusion of road segments due to foliage, z-ordering of freeways, tunnels, bridges, buildings, and other geospatial entities may be determined, validated, and corrected. A learning algorithm can be trained with image-based descriptors that encode visible data consistencies. After training, the algorithm can classify errors and inconsistencies using combinations of different descriptors such as color, texture, image-gradients, and filter responses.
    • 这里描述了用于使用与地球表面倾斜的角度拍摄的倾斜图像或航空照片来验证和校正地图数据的技术。 可以分析倾斜图像中的像素以检测,验证和校正生成地图中使用的其他数据源,如矢量数据,高程图,投影参数和三维模型数据。 可以分析斜视图中的可视性和遮挡信息,以减少闭塞或闭塞实体中的误差。 可以确定,验证和纠正由于树叶,高速公路,隧道,桥梁,建筑物和其他地理空间实体造成的路段堵塞。 可以使用编码可视数据一致性的基于图像的描述符来训练学习算法。 训练后,该算法可以使用不同描述符(如颜色,纹理,图像梯度和过滤器响应)的组合来分类错误和不一致。
    • 4. 发明申请
    • OBLIQUE DISPLAY WITH ADDITIONAL DETAIL
    • 带附加细节的OBLIQUE显示
    • US20100085350A1
    • 2010-04-08
    • US12244435
    • 2008-10-02
    • Pragyana K. MishraEyal OfekGur Kimchi
    • Pragyana K. MishraEyal OfekGur Kimchi
    • G06T15/00
    • G06T15/00G01C21/3638G01C21/3673G06T17/05
    • A method and system of creating an oblique display with additional detail such as texture and labels is disclosed. The footprint of objects on the image on a digital elevation map may be determined and an outline of the objects may be determined by creating object polygons that outline the bounds of the objects. The objects that are visible in the image and the objects that are occluded are determined using the footprint of the objects and the object polygons. The occluded object sections may be displayed in a modified form as part of the occluding object. Label display locations may be evaluated for objects to determine an optimal label display location based on a label criteria function and labels may be added to the objects in the image at the optimal label display location.
    • 公开了一种创建具有附加细节(如纹理和标签)的倾斜显示器的方法和系统。 可以确定数字高程图上的图像上的对象的占用面积,并且可以通过创建概述对象的边界的对象多边形来确定对象的轮廓。 使用对象和对象多边形的覆盖区确定在图像中可见的对象和被遮挡的对象。 封闭对象部分可以以修改形式显示为封闭对象的一部分。 可以针对对象评估标签显示位置,以基于标签标准函数来确定最佳标签显示位置,并且可以在最佳标签显示位置处将图像中的标签添加到标签。
    • 5. 发明申请
    • VALIDATION AND CORRECTION OF MAP DATA USING OBLIQUE IMAGES
    • 使用OBLIQUE图像验证和校正地图数据
    • US20100074538A1
    • 2010-03-25
    • US12237817
    • 2008-09-25
    • Pragyana K. MishraEyal OfekGur Kimchi
    • Pragyana K. MishraEyal OfekGur Kimchi
    • G06K9/62
    • G06K9/6286G06T7/0002G06T17/05G06T2207/10032
    • Technologies are described herein for validating and correcting map data using oblique images or aerial photographs taken at oblique angles to the earth's surface. Pixels within oblique images can be analyzed to detect, validate, and correct other sources of data used in generating maps such as vector data, elevation maps, projection parameters, and three-dimensional model data. Visibility and occlusion information in oblique views may be analyzed to reduce errors in either occluding or occluded entities. Occlusion of road segments due to foliage, z-ordering of freeways, tunnels, bridges, buildings, and other geospatial entities may be determined, validated, and corrected. A learning algorithm can be trained with image-based descriptors that encode visible data consistencies. After training, the algorithm can classify errors and inconsistencies using combinations of different descriptors such as color, texture, image-gradients, and filter responses.
    • 这里描述了用于使用与地球表面倾斜的角度拍摄的倾斜图像或航空照片来验证和校正地图数据的技术。 可以分析倾斜图像中的像素以检测,验证和校正生成地图中使用的其他数据源,如矢量数据,高程图,投影参数和三维模型数据。 可以分析斜视图中的可视性和遮挡信息,以减少闭塞或闭塞实体中的误差。 可以确定,验证和纠正由于树叶,高速公路,隧道,桥梁,建筑物和其他地理空间实体造成的路段堵塞。 可以使用编码可视数据一致性的基于图像的描述符来训练学习算法。 训练后,该算法可以使用不同描述符(如颜色,纹理,图像梯度和过滤器响应)的组合来分类错误和不一致。
    • 10. 发明授权
    • Depersonalizing location traces
    • 个性化位置痕迹
    • US08463289B2
    • 2013-06-11
    • US13163396
    • 2011-06-17
    • Gil ShklarskiBrian BeckmanEyal OfekKenn Daniel CartierShai HerzogGur KimchiBernard Lawrence Johnston
    • Gil ShklarskiBrian BeckmanEyal OfekKenn Daniel CartierShai HerzogGur KimchiBernard Lawrence Johnston
    • H04W24/00
    • H04W12/02H04W64/00H04W88/08
    • Positional information is provided while minimizing the possibility that personally identifiable information can be derived therefrom. Positional information is received in the form of trails that can be aggregated. Individual cells of a grid reflect a quantity of aggregated trails through those cells, an average intensity and direction of movement through those cells, or a more detailed distribution thereof. Alternatively, individual trails are aggregated to an aggregated trail in the form of a line. Further obfuscation of personally identifiable information occurs by resampling aggregated positional information, by introducing false positional information, or by falsely modifying existing positional information, in a manner that does not impact the overall aggregations, and by pruning, or deleting, positional information, especially around sensitive locations, such as a user's home, place of business, or other location that users typically would seek to keep private. Provision of positional information is delayed until a sufficient amount is received.
    • 提供位置信息,同时最小化可以从其导出个人身份信息的可能性。 以可聚合的路径的形式收到位置信息。 网格的单个细胞反映了通过这些细胞的聚集迹线的数量,通过这些细胞的平均强度和移动方向,或其更详细的分布。 或者,单个路径将以行的形式聚合到聚合路径。 对个人识别信息的进一步模糊发生是通过重新采样聚合的位置信息,引入错误的位置信息,或以不影响总体聚集的方式错误地修改现有的位置信息,以及通过修剪或删除位置信息,特别是在 敏感位置,例如用户的家庭,营业地点或用户通常将寻求保密的其他位置。 提供位置信息被延迟直到接收到足够的量。