PROVIDING POINTS OF INTEREST TO USER DEVICES IN VARIABLE ZONES
    11.
    发明申请
    PROVIDING POINTS OF INTEREST TO USER DEVICES IN VARIABLE ZONES 有权
    向可变区域中的用户设备提供兴趣点

    公开(公告)号:US20150100271A1

    公开(公告)日:2015-04-09

    申请号:US14572755

    申请日:2014-12-16

    Applicant: GOOGLE INC.

    Abstract: Receiving point of interest zones and alerts on user devices comprises communicating, by a user computing device to a remote computing device, a request for point of interest data corresponding to points of interest within a proximity of the user device; presenting the received point of interest data; identifying a particular point of interest; and outputting an alert regarding the particular point of interest. Receiving point of interest zones on user devices comprises communicating a request for point of interest data; receiving the point of interest data from the remote network device wherein a size of the point of interest zone is determined based on a density of points of interest in the proximity of the user, and wherein the shape of the point of interest zone is expanded in a direction of travel and contracted in the opposite direction; and presenting the received point of interest data.

    Abstract translation: 在用户设备上接收兴趣点区域和警报包括由用户计算设备向远程计算设备传达对应于用户设备附近的兴趣点的兴趣点数据的请求; 呈现接收的兴趣点数据; 识别一个特定的兴趣点; 并输出关于特定兴趣点的警报。 在用户设备上接收兴趣点区域包括传送关于兴趣点数据的请求; 从所述远程网络设备接收所述兴趣点数据,其中,基于所述用户附近的兴趣点的密度来确定所述兴趣点区域的大小,并且其中所述兴趣点区域的形状在 旅行方向与方向相反; 并呈现所接收的兴趣点数据。

    Extracting Card Data Using Three-Dimensional Models
    12.
    发明申请
    Extracting Card Data Using Three-Dimensional Models 审中-公开
    使用三维模型提取卡片数据

    公开(公告)号:US20150006361A1

    公开(公告)日:2015-01-01

    申请号:US14026781

    申请日:2013-09-13

    Applicant: GOOGLE INC.

    Abstract: Comparing extracted card data from a continuous scan comprises receiving, by one or more computing devices, a digital scan of a card; obtaining a plurality of images of the card from the digital scan of the physical card; performing an optical character recognition algorithm on each of the plurality of images; comparing results of the application of the optical character recognition algorithm for each of the plurality of images; determining if a configured threshold of the results for each of the plurality of images match each other; and verifying the results when the results for each of the plurality of images match each other. Threshold confidence level for the extracted card data can be employed to determine the accuracy of the extraction. Data is further extracted from blended images and three-dimensional models of the card. Embossed text and holograms in the images may be used to prevent fraud.

    Abstract translation: 比较来自连续扫描的提取的卡数据包括由一个或多个计算设备接收卡的数字扫描; 从所述物理卡的数字扫描中获取所述卡的多个图像; 对所述多个图像中的每一个执行光学字符识别算法; 比较针对所述多个图像中的每一个的所述光学字符识别算法的应用结果; 确定所述多个图像中的每一个的结果的配置阈值是否彼此匹配; 以及当多个图像中的每一个的结果彼此匹配时验证结果。 可以采用提取的卡数据的阈值置信水平来确定提取的准确性。 从混合图像和卡片的三维模型进一步提取数据。 图像中的压纹文字和全息图可能被用来防止欺诈。

    CLUSTERING GEOFENCE-BASED ALERTS FOR MOBILE DEVICES
    13.
    发明申请
    CLUSTERING GEOFENCE-BASED ALERTS FOR MOBILE DEVICES 有权
    用于移动设备的基于GEOPENCE的警报

    公开(公告)号:US20150005012A1

    公开(公告)日:2015-01-01

    申请号:US14329812

    申请日:2014-07-11

    Applicant: GOOGLE INC.

    CPC classification number: H04W4/021 G06F17/3087 G08B1/08 H04W4/12 H04W64/003

    Abstract: A geofence management system obtains location data for points of interest. The geofence management system determines, at the option of the user, the location of a user mobile computing device relative to specific points of interest and alerts the user when the user nears the points of interest. The geofence management system, however, determines relationships among the identified points of interest, and associates or “clusters” the points of interest together based on the determined relationships. Rather than establishing separate geofences for multiple points of interest, and then alerting the user each time the user's mobile device enters each geofence boundary, the geofence management system establishes a single geofence boundary for the associated points of interest. When the user's mobile device enters the clustered geofence boundary, the geofence management system notifies the user device to alert the user of the entrance event. The user then receives the clustered, geofence-based alert.

    Abstract translation: 地理围栏管理系统获取兴趣点的位置数据。 地理围栏管理系统可以根据用户的选择确定用户移动计算设备相对于特定兴趣点的位置,并且在用户接近兴趣点时提醒用户。 然而,地理围栏管理系统根据所确定的关系确定所识别的兴趣点之间的关系,以及关联点或“聚集”兴趣点在一起。 而不是为多个兴趣点建立单独的地理围栏,然后每当用户的移动设备进入每个地理围栏边界时提醒用户,地理围栏管理系统为相关联的兴趣点建立单一的地理围栏边界。 当用户的移动设备进入群集地理围栏边界时,地理围栏管理系统通知用户设备提醒用户入口事件。 然后,用户接收基于地理位置的群集警报。

    Extracting card data with card models
    16.
    发明授权
    Extracting card data with card models 有权
    使用卡片型号提取卡片数据

    公开(公告)号:US08831329B1

    公开(公告)日:2014-09-09

    申请号:US14059151

    申请日:2013-10-21

    Applicant: Google Inc.

    Abstract: Embodiments herein provide computer-implemented techniques for allowing a user computing device to extract financial card information using optical character recognition (“OCR”). Extracting financial card information may be improved by applying various classifiers and other transformations to the image data. For example, applying a linear classifier to the image to determine digit locations before applying the OCR algorithm allows the user computing device to use less processing capacity to extract accurate card data. The OCR application may train a classifier to use the wear patterns of a card to improve OCR algorithm performance. The OCR application may apply a linear classifier and then a nonlinear classifier to improve the performance and the accuracy of the OCR algorithm. The OCR application uses the known digit patterns used by typical credit and debit cards to improve the accuracy of the OCR algorithm.

    Abstract translation: 这里的实施例提供了计算机实现的技术,用于允许用户计算设备使用光学字符识别(“OCR”)提取金融卡信息。 可以通过对图像数据应用各种分类器和其他变换来提高金融卡信息的提取。 例如,在应用OCR算法之前,对图像应用线性分类器以确定数字位置允许用户计算设备使用较少的处理能力来提取准确的卡数据。 OCR应用程序可以训练分类器来使用卡的磨损模式来改善OCR算法性能。 OCR应用可以应用线性分类器,然后应用非线性分类器来提高OCR算法的性能和准确性。 OCR应用程序使用典型的信用卡和借记卡使用的已知数字模式来提高OCR算法的准确性。

    Extracting card data for simultaneous display with an image

    公开(公告)号:US10387742B2

    公开(公告)日:2019-08-20

    申请号:US15342116

    申请日:2016-11-02

    Applicant: GOOGLE INC.

    Abstract: Extracting card data comprises receiving, by one or more computing devices, a digital image of a card; perform an image recognition process on the digital representation of the card; identifying an image in the digital representation of the card; comparing the identified image to an image database comprising a plurality of images and determining that the identified image matches a stored image in the image database; determining a card type associated with the stored image and associating the card type with the card based on the determination that the identified image matches the stored image; and performing a particular optical character recognition algorithm on the digital representation of the card, the particular optical character recognition algorithm being based on the determined card type. Another example superimposes the extracted data directly above, below, or beside the corresponding section on the displayed image.

    Inferring purchase intent using non-payment transaction events

    公开(公告)号:US10096037B2

    公开(公告)日:2018-10-09

    申请号:US14595193

    申请日:2015-01-12

    Applicant: GOOGLE INC.

    Abstract: Inferring purchase intent using non-payment transaction signals predicts whether a payment transaction has been completed based on non-payment information. An account system that operates outside of the payment path does not take part in and the approval of a financial transaction between the user and the merchant system, distributes an offer to the user. The user completes a financial payment transaction with the merchant and the account system determines whether a trigger event has occurred. The user performs an action or enters information using the user computing device, and the user computing device transmits an indication of the action to the account system. In another example, the account system receives notification from another system or device. The account system determines whether the action is a trigger event and the predictive model determines whether the user completed a financial transaction and/or redeemed the distributed offer.

    Extracting card identification data

    公开(公告)号:US09886641B2

    公开(公告)日:2018-02-06

    申请号:US15267117

    申请日:2016-09-15

    Applicant: GOOGLE INC.

    Abstract: Extracting card information comprises a server at an optical character recognition (“OCR”) system that interprets data from a card. The OCR system performs an optical character recognition algorithm an image of a card and performs a data recognition algorithm on a machine-readable code on the image of the card. The OCR system compares a series of extracted alphanumeric characters obtained via the optical character recognition process to data extracted from the machine-readable code via the data recognition process and matches the alphanumeric series of characters to a particular series of characters extracted from the machine-readable code. The OCR system determines if the alphanumeric series and the matching series of characters extracted from the machine-readable code comprise any discrepancies and corrects the alphanumeric series of characters based on the particular series of characters extracted from the machine-readable code upon a determination that a discrepancy exists.

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