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    • 21. 发明申请
    • System and Method for Fusing Geospatial Data
    • 用于融合地理空间数据的系统和方法
    • US20110280453A1
    • 2011-11-17
    • US13158301
    • 2011-06-10
    • Ching-Chien ChenDipsy KapoorCraig A. KnoblockCyrus Shahabi
    • Ching-Chien ChenDipsy KapoorCraig A. KnoblockCyrus Shahabi
    • G06K9/46
    • G06T7/75G06T2207/10032G06T2207/30184
    • Automatic conflation systems and techniques which provide vector-imagery conflation and map-imagery conflation. Vector-imagery conflation is an efficient approach that exploits knowledge from multiple data sources to identify a set of accurate control points. Vector-imagery conflation provides automatic and accurate alignment of various vector datasets and imagery, and is appropriate for GIS applications, for example, requiring alignment of vector data and imagery over large geographical regions. Map-imagery conflation utilizes common vector datasets as “glue” to automatically integrate street maps with imagery. This approach provides automatic, accurate, and intelligent images that combine the visual appeal and accuracy of imagery with the detailed attribution information often contained in such diverse maps. Both conflation approaches are applicable for GIS applications requiring, for example, alignment of vector data, raster maps, and imagery. If desired, the conflated data generated by such systems may be retrieved on-demand.
    • 自动融合系统和技术,提供矢量图像融合和地图图像融合。 矢量图像混合是一种有效的方法,利用来自多个数据源的知识来识别一组精确的控制点。 矢量图像融合提供了各种矢量数据集和图像的自动和准确对齐,适用于GIS应用,例如,需要在大地理区域上对齐矢量数据和图像。 地图图像融合利用常用的矢量数据集作为“胶合”,自动将街道地图与图像整合。 这种方法提供自动,准确和智能的图像,将图像的视觉吸引力和准确性与通常包含在这种不同地图中的详细归属信息相结合。 两种融合方法都适用于需要例如矢量数据,光栅图和图像对齐的GIS应用。 如果需要,可以根据需要检索由这样的系统生成的混合数据。
    • 24. 发明授权
    • Dynamically linking relevant documents to regions of interest
    • 将相关文件动态链接到感兴趣的地区
    • US08635228B2
    • 2014-01-21
    • US12619554
    • 2009-11-16
    • Cyrus ShahabiCraig A. KnoblockDipsy KapoorChing-Chien Chen
    • Cyrus ShahabiCraig A. KnoblockDipsy KapoorChing-Chien Chen
    • G06F7/00G06F17/30
    • G06F17/3087G06F17/30722G06Q30/00
    • Document relevance is determined with respect to a region of interest (ROI). A set of location references may be associated with a set of documents. The system selects location references associated with an ROI and then selects documents corresponding to the selected location references. The selected documents can be reported or processed further. A document-location reference index can be accessed when the present system is ‘online’ and processing a request for documents relevant to an ROI. The document-location reference index may be generated and updated while the present system is ‘offline’ and not processing a request for documents. The resulting relevant documents may be provided to a user in response to a document search associated with the ROI or along with an advertisement associated with the ROI.
    • 相对于感兴趣区域(ROI)确定文档相关性。 一组位置引用可以与一组文档相关联。 系统选择与ROI相关联的位置参考,然后选择与所选位置参考相对应的文档。 所选文件可以进一步报告或处理。 当本系统“联机”并处理与ROI有关的文件的请求时,可以访问文档位置参考索引。 文档位置参考索引可以在当前系统“脱机”时生成和更新,而不处理对文档的请求。 可以响应于与ROI相关联的文档搜索或与ROI相关联的广告来将所得到的相关文档提供给用户。
    • 25. 发明授权
    • Blind evaluation of nearest neighbor queries wherein locations of users are transformed into a transformed space using a plurality of keys
    • 使用多个密钥将用户的位置变换成变换空间的最近邻查询的盲评估
    • US08099380B1
    • 2012-01-17
    • US12129629
    • 2008-05-29
    • Cyrus ShahabiJaffar KhoshgozaranHoutan Shirani-Mehr
    • Cyrus ShahabiJaffar KhoshgozaranHoutan Shirani-Mehr
    • G06F15/00
    • H04W4/023H04W12/02
    • Systems and techniques are described for blind evaluation of nearest neighbor queries. Locations of multiple users in an original space are received. The locations in the original space are encoded into encoded locations in a transformed space. A relative proximity of the encoded locations in the transformed space is maintained after the encoding. Multiple keys corresponding to the multiple users are generated. Each key enables a reverse transformation of an encoded user location in the transformed space to an original user location in the original space. The multiple keys are provided to the corresponding multiple users, and the encoded locations in the transformed space are provided to a device. An order of computations required to reverse transform the encoded locations in the transformed space to the locations in the original space in the absence of a key is greater than a computational threshold.
    • 描述了对最近邻查询的盲评估的系统和技术。 收到原始空间中多个用户的位置。 原始空间中的位置被编码为变换空间中的编码位置。 在编码之后,维持变换空间中编码位置的相对接近度。 生成与多个用户对应的多个密钥。 每个键使得经变换的空间中的编码用户位置反向变换为原始空间中的原始用户位置。 将多个键提供给相应的多个用户,并将变换的空间中的编码位置提供给设备。 在不存在密钥的情况下将经变换的空间中的编码位置反向变换为原始空间中的位置所需的计算顺序大于计算阈值。
    • 26. 发明申请
    • PRECISELY LOCATING FEATURES ON GEOSPATIAL IMAGERY
    • 精确的地理图像的位置特征
    • US20110007941A1
    • 2011-01-13
    • US12501242
    • 2009-07-10
    • Ching-Chien ChenDipsy KapoorCraig A. KnoblockCyrus Shahabi
    • Ching-Chien ChenDipsy KapoorCraig A. KnoblockCyrus Shahabi
    • G06K9/62
    • G06T7/75G06T2207/10032G06T2207/30184
    • Methods for locating a feature on geospatial imagery and systems for performing those methods are disclosed. An accuracy level of each of a plurality of geospatial vector datasets available in a database can be determined. Each of the plurality of geospatial vector datasets corresponds to the same spatial region as the geospatial imagery. The geospatial vector dataset having the highest accuracy level may be selected. When the selected geospatial vector dataset and the geospatial imagery are misaligned, the selected geospatial vector dataset is aligned to the geospatial imagery. The location of the feature on the geospatial imagery is then determined based on the selected geospatial vector dataset and outputted via a display device.
    • 公开了用于定位地理空间图像特征的方法和用于执行这些方法的系统。 可以确定数据库中可用的多个地理空间矢量数据集中的每一个的精度水平。 多个地理空间矢量数据集中的每一个对应于与地理空间图像相同的空间区域。 可以选择具有最高精度水平的地理空间矢量数据集。 当所选择的地理空间矢量数据集和地理空间图像不对齐时,所选择的地理空间矢量数据集与地理空间图像相一致。 然后,基于所选择的地理空间矢量数据集确定地理空间图像上的特征的位置,并通过显示装置输出。
    • 28. 发明授权
    • System and method for fusing geospatial data
    • 用于融合地理空间数据的系统和方法
    • US07660441B2
    • 2010-02-09
    • US11169076
    • 2005-06-28
    • Ching-Chien ChenCraig A. KnoblockCyrus ShahabiYao-Yi Chiang
    • Ching-Chien ChenCraig A. KnoblockCyrus ShahabiYao-Yi Chiang
    • G06K9/32G06K9/46
    • G06K9/0063G06T3/0075G06T7/33
    • Automatic conflation systems and techniques which provide vector-imagery conflation and map-imagery conflation. Vector-imagery conflation is an efficient approach that exploits knowledge from multiple data sources to identify a set of accurate control points. Vector-imagery conflation provides automatic and accurate alignment of various vector datasets and imagery, and is appropriate for GIS applications, for example, requiring alignment of vector data and imagery over large geographical regions. Map-imagery conflation utilizes common vector datasets as “glue” to automatically integrate street maps with imagery. This approach provides automatic, accurate, and intelligent images that combine the visual appeal and accuracy of imagery with the detailed attribution information often contained in such diverse maps. Both conflation approaches are applicable for GIS applications requiring, for example, alignment of vector data, raster maps, and imagery. If desired, the conflated data generated by such systems may be retrieved on-demand.
    • 自动融合系统和技术,提供矢量图像融合和地图图像融合。 矢量图像混合是一种有效的方法,利用来自多个数据源的知识来识别一组精确的控制点。 矢量图像融合提供了各种矢量数据集和图像的自动和准确对齐,适用于GIS应用,例如,需要在大地理区域上对齐矢量数据和图像。 地图图像融合利用常用的矢量数据集作为“胶合”,自动将街道地图与图像整合。 这种方法提供自动,准确和智能的图像,将图像的视觉吸引力和准确性与通常包含在这种不同地图中的详细归属信息相结合。 两种融合方法都适用于需要例如矢量数据,光栅图和图像对齐的GIS应用。 如果需要,可以根据需要检索由这样的系统生成的混合数据。
    • 30. 发明申请
    • Automatically and accurately conflating road vector data, street maps, and orthoimagery
    • 自动准确地混合道路矢量数据,街道地图和正交摄像
    • US20070014488A1
    • 2007-01-18
    • US11169076
    • 2005-06-28
    • Ching-Chien ChenCraig KnoblockCyrus ShahabiYao-Yi Chiang
    • Ching-Chien ChenCraig KnoblockCyrus ShahabiYao-Yi Chiang
    • G06K9/32G06K9/46
    • G06K9/0063G06T3/0075G06T7/33
    • Automatic conflation systems and techniques which provide vector-imagery conflation and map-imagery conflation. Vector-imagery conflation is an efficient approach that exploits knowledge from multiple data sources to identify a set of accurate control points. Vector-imagery conflation provides automatic and accurate alignment of various vector datasets and imagery, and is appropriate for GIS applications, for example, requiring alignment of vector data and imagery over large geographical regions. Map-imagery conflation utilizes common vector datasets as “glue” to automatically integrate street maps with imagery. This approach provides automatic, accurate, and intelligent images that combine the visual appeal and accuracy of imagery with the detailed attribution information often contained in such diverse maps. Both conflation approaches are applicable for GIS applications requiring, for example, alignment of vector data, raster maps, and imagery. If desired, the conflated data generated by such systems may be retrieved on-demand.
    • 自动融合系统和技术,提供矢量图像融合和地图图像融合。 矢量图像混合是一种有效的方法,利用来自多个数据源的知识来识别一组精确的控制点。 矢量图像融合提供了各种矢量数据集和图像的自动和准确对齐,适用于GIS应用,例如,需要在大地理区域上对齐矢量数据和图像。 地图图像融合利用常用的矢量数据集作为“胶合”,自动将街道地图与图像整合。 这种方法提供自动,准确和智能的图像,将图像的视觉吸引力和准确性与通常包含在这种不同地图中的详细归属信息相结合。 两种融合方法都适用于需要例如矢量数据,光栅图和图像对齐的GIS应用。 如果需要,可以根据需要检索由这样的系统生成的混合数据。