公开(公告)号：US09367756B2

公开(公告)日：2016-06-14

申请号：US14254242

申请日：2014-04-16

Applicant: Google Inc.

Inventor： Anand Pillai ,  Andrew Rabinovich

IPC: G06K9/00 ,  G06K9/46 ,  G06K9/62

CPC classification number: G06K9/46 ,  G06K9/00288 ,  G06K9/6218 ,  G06K9/622

Abstract: Methods and systems for selecting a representative image of an entity are disclosed. According to one embodiment, a computer-implemented method for selecting a representative image of an entity is disclosed. The method includes: accessing a collection of images of the entity; clustering, based on similarity of one or more similarity features, images from the collection to form a plurality of similarity clusters; and selecting the representative image from one of said similarity clusters. Further, based on cluster size of said similarity clusters popular clusters can be determined, and the selection of the representative image can be from the popular clusters. In addition, the method can further include assigning a headshot score based upon a portion of the respective image covered by the entity to respective images in said popular clusters, and further selecting the representative image based upon the headshot score.

Abstract translation: 公开了用于选择实体的代表性图像的方法和系统。 根据一个实施例，公开了一种用于选择实体的代表性图像的计算机实现的方法。 该方法包括：访问该实体的图像集合; 基于一个或多个相似性特征的相似性，聚集来自所述集合的图像以形成多个相似性聚类; 以及从所述相似性集群之一选择所述代表图像。 此外，基于所述相似度簇的簇大小，可以确定流行簇，并且可以从流行簇中选择代表图像。 此外，该方法可以进一步包括基于由该实体覆盖的各个图像的一部分将所述流行集群中的各个图像分配头像分数，以及基于所述头像分数进一步选择所述代表图像。

公开(公告)号：US08661053B2

公开(公告)日：2014-02-25

申请号：US13674483

申请日：2012-11-12

Applicant: Google Inc.

Inventor： John Flynn ,  Dragomir Anguelov ,  Hartmut Neven ,  Mark Cummins ,  James Philbin ,  Rafael Spring ,  Hartwig Adam ,  Anand Pillai

IPC: G06F17/30

CPC classification number: G06F17/30268 ,  G06F17/30247 ,  G06F17/3028

Abstract: A method and apparatus for enabling virtual tags is described. The method may include receiving a first digital image data and virtual tag data to be associated with a real-world object in the first digital image data, wherein the first digital image data is captured by a first mobile device, and the virtual tag data includes metadata received from a user of the first mobile device. The method may also include generating a first digital signature from the first digital image data that describes the real-world object, and in response to the generation, inserting in substantially real-time the first digital signature into a searchable index of digital images. The method may also include storing, in a tag database, the virtual tag data and an association between the virtual tag data and the first digital signature inserted into the index of digital images.

Abstract translation: 描述了一种用于启用虚拟标签的方法和装置。 该方法可以包括在第一数字图像数据中接收与真实世界对象相关联的第一数字图像数据和虚拟标签数据，其中第一数字图像数据由第一移动设备捕获，并且虚拟标签数据包括 从第一移动设备的用户接收的元数据。 该方法还可以包括从描述真实世界对象的第一数字图像数据生成第一数字签名，并且响应于生成，基本上实时地将第一数字签名插入到可搜索的数字图像索引中。 该方法还可以包括在标签数据库中存储虚拟标签数据以及虚拟标签数据与插入数字图像索引中的第一数字签名之间的关联。

公开(公告)号：US20150169611A1

公开(公告)日：2015-06-18

申请号：US14526612

申请日：2014-10-29

Applicant: Google Inc.

Inventor： James William Philbin ,  Anand Pillai ,  John Flynn ,  Hartwig Adam

IPC: G06F17/30

CPC classification number: G06F17/30153 ,  G06F17/30247 ,  G06F17/30256 ,  G06F17/30864

Abstract: Systems and methods for a dynamic visual search engine are provided. In one example method, a criteria used to partition a set of compressed image descriptors into multiple database shards may be determined. Additionally, a size of a dynamic index may be determined. The dynamic index may represent a dynamic number of images and may be configured to accept insertion of reference images into the dynamic index that can be search against immediately. According to the method, an instruction to merge the uncompressed image descriptors of the dynamic index into the database shards of the compressed image descriptors may be received, and the uncompressed image descriptors of the dynamic index may be responsively merged into the database shards of the compressed image descriptors based on the criteria.

Abstract translation: 提供了动态视觉搜索引擎的系统和方法。 在一个示例性方法中，可以确定用于将一组压缩图像描述符分割成多个数据库分片的标准。 另外，可以确定动态索引的大小。 动态索引可以表示动态数量的图像，并且可以被配置为接受将参考图像插入到可以立即搜索的动态索引中。 根据该方法，可以接收将动态索引的未压缩图像描述符合并到压缩图像描述符的数据库碎片中的指令，并且动态索引的未压缩图像描述符可以被响应地合并到压缩的图像描述符的数据库碎片中 基于标准的图像描述符。

公开(公告)号：US09442950B2

公开(公告)日：2016-09-13

申请号：US14526612

申请日：2014-10-29

Applicant: Google Inc.

Inventor： James William Philbin ,  Anand Pillai ,  John Flynn ,  Hartwig Adam

IPC: G06F17/30

CPC classification number: G06F17/30153 ,  G06F17/30247 ,  G06F17/30256 ,  G06F17/30864

Abstract: Systems and methods for a dynamic visual search engine are provided. In one example method, a criteria used to partition a set of compressed image descriptors into multiple database shards may be determined. Additionally, a size of a dynamic index may be determined. The dynamic index may represent a dynamic number of images and may be configured to accept insertion of reference images into the dynamic index that can be search against immediately. According to the method, an instruction to merge the uncompressed image descriptors of the dynamic index into the database shards of the compressed image descriptors may be received, and the uncompressed image descriptors of the dynamic index may be responsively merged into the database shards of the compressed image descriptors based on the criteria.

Abstract translation: 提供了动态视觉搜索引擎的系统和方法。 在一个示例性方法中，可以确定用于将一组压缩图像描述符分割成多个数据库分片的标准。 另外，可以确定动态索引的大小。 动态索引可以表示动态数量的图像，并且可以被配置为接受将参考图像插入到可以立即搜索的动态索引中。 根据该方法，可以接收将动态索引的未压缩图像描述符合并到压缩图像描述符的数据库碎片中的指令，并且动态索引的未压缩图像描述符可以被响应地合并到压缩的图像描述符的数据库碎片中 基于标准的图像描述符。

公开(公告)号：US20150169978A1

公开(公告)日：2015-06-18

申请号：US14254242

申请日：2014-04-16

Applicant: Google Inc.

Inventor： Anand Pillai ,  Andrew Rabinovich

IPC: G06K9/46 ,  G06K9/62

CPC classification number: G06K9/46 ,  G06K9/00288 ,  G06K9/6218 ,  G06K9/622

Abstract: Methods and systems for selecting a representative image of an entity are disclosed. According to one embodiment, a computer-implemented method for selecting a representative image of an entity is disclosed. The method includes: accessing a collection of images of the entity; clustering, based on similarity of one or more similarity features, images from the collection to form a plurality of similarity clusters; and selecting the representative image from one of said similarity clusters. Further, based on cluster size of said similarity clusters popular clusters can be determined, and the selection of the representative image can be from the popular clusters. In addition, the method can further include assigning a headshot score based upon a portion of the respective image covered by the entity to respective images in said popular clusters, and further selecting the representative image based upon the headshot score.

Abstract translation: 公开了用于选择实体的代表性图像的方法和系统。 根据一个实施例，公开了一种用于选择实体的代表图像的计算机实现的方法。 该方法包括：访问该实体的图像集合; 基于一个或多个相似性特征的相似性，聚集来自所述集合的图像以形成多个相似性聚类; 以及从所述相似性集群之一选择所述代表图像。 此外，基于所述相似度簇的簇大小，可以确定流行的簇，并且可以从流行簇中选择代表图像。 此外，该方法可以进一步包括基于由该实体覆盖的各个图像的一部分将所述流行集群中的各个图像分配头像分数，以及基于所述头像分数进一步选择所述代表图像。