公开(公告)号：WO2012122069A2

公开(公告)日：2012-09-13

申请号：PCT/US2012/027643

申请日：2012-03-04

Applicant: MICROSOFT CORPORATION

Inventor： LEICHTER, Ido ,  KRUPKA, Eyal ,  ABRAMOVSKI, Igor ,  KVIATKOVSKY, Igor

IPC: G06T7/00 ,  G06K9/46

CPC classification number: G06T7/20 ,  G06T2207/10016 ,  G06T2207/30201 ,  G06T2207/30241

Abstract: A facial detecting system may analyze a video by traversing the video forwards and backwards to create tracks of a person within the video. After separating the video into shots, the frames of each shot may be analyzed using a face detector algorithm to produce some analyzed information for each frame. A facial track may be generated by grouping the faces detected and by traversing the sequence of frames forwards and backwards. Facial tracks may be joined together within a shot to generate a single track for a person's face within the shot, even when the tracks are discontinuous.

Abstract translation: 面部检测系统可以通过向前和向后遍历视频来分析视频，以创建视频内的人的轨道。 在将视频分离成镜头后，可以使用面部检测器算法分析每个镜头的帧，以产生每个帧的一些分析信息。 可以通过对检测到的面进行分组并且向前和向后遍历帧序列来生成面部轨迹。 即使在轨道不连续的情况下，面部轨迹也可以在镜头内连接在一起，以在镜头内为人脸部生成单个轨迹。

公开(公告)号：WO2011109250A2

公开(公告)日：2011-09-09

申请号：PCT/US2011/026356

申请日：2011-02-25

Applicant: MICROSOFT CORPORATION

Inventor： KRUPKA, Eyal ,  ABRAMOVSKI, Igor ,  KVIATKOVSKY, Igor

CPC classification number: G06K9/6218 ,  G06F17/30259 ,  G06K9/00288 ,  G06K9/00677 ,  G06K9/623 ,  G06K2009/00328 ,  G06K2209/27

Abstract: A user's collection of images may be analyzed to identify people's faces within the images, then create clusters of similar faces, where each of the clusters may represent a person. The clusters may be ranked in order of size to determine a relative importance of the associated person to the user. The ranking may be used in many social networking applications to filter and present content that may be of interest to the user. In one use scenario, the clusters may be used to identify images from a second user's image collection, where the identified images may be pertinent or interesting to the first user. The ranking may also be a function of user interactions with the images, as well as other input not related to the images. The ranking may be incrementally updated when new images are added to the user's collection.

Abstract translation: 可以分析用户的图像集合以识别图像内的人脸，然后创建类似面孔的群集，其中每个群集可以代表一个人。 可以按照大小的顺序对簇进行排序，以确定相关联的人对用户的相对重要性。 该排名可以用于许多社交网络应用中以过滤和呈现用户可能感兴趣的内容。 在一个使用场景中，群集可以用于识别来自第二用户的图像集合的图像，其中识别的图像可能与第一用户相关或有趣。 排名也可能是用户与图像的交互作用以及与图像无关的其他输入的功能。 当将新图像添加到用户的集合中时，排名可以逐步更新。

公开(公告)号：WO2014059201A1

公开(公告)日：2014-04-17

申请号：PCT/US2013/064420

申请日：2013-10-11

Applicant: MICROSOFT CORPORATION

Inventor： KRUPKA, Eyal ,  LEYVAND, Tommer ,  KVIATKOVSKY, Igor ,  ABRAMOVSKI, Igor ,  KEOSABABIAN, Tim ,  LI, Jinyu

IPC: G06K9/00 ,  G06K9/46

CPC classification number: G06K9/00228 ,  G06K9/4661 ,  G06T5/002

Abstract: Methods for face recognition are provided. In one example, a method for face recognition includes receiving a user image and detecting a user luminance of data representing the user's face. An adaptive low pass filter is selected that corresponds to the user luminance of the user's face. The filter is applied to the user image to create a filtered user image. The filtered user image is projected to create a filtered user image representation. A filtered reference image representation that has been filtered with the same low pass filter is selected from a reference image database. The method then determines whether the filtered reference image representation matches the filtered user image representation.

Abstract translation: 提供面部识别方法。 在一个示例中，一种用于人脸识别的方法包括：接收用户图像并检测表示用户脸部的数据的用户亮度。 选择对应于用户脸部的用户亮度的自适应低通滤波器。 过滤器应用于用户图像以创建过滤的用户图像。 投影过滤的用户图像以创建过滤的用户图像表示。 从参考图像数据库中选择已经用相同的低通滤波器滤波的滤波的参考图像表示。 该方法然后确定滤波的参考图像表示是否与滤波的用户图像表示匹配。

公开(公告)号：EP2681717A2

公开(公告)日：2014-01-08

申请号：EP12755538.1

申请日：2012-03-04

Applicant: Microsoft Corporation

Inventor： LEICHTER, Ido ,  KRUPKA, Eyal ,  ABRAMOVSKI, Igor ,  KVIATKOVSKY, Igor

IPC: G06T7/00 ,  G06K9/46

CPC classification number: G06T7/20 ,  G06T2207/10016 ,  G06T2207/30201 ,  G06T2207/30241

Abstract: A facial detecting system may analyze a video by traversing the video forwards and backwards to create tracks of a person within the video. After separating the video into shots, the frames of each shot may be analyzed using a face detector algorithm to produce some analyzed information for each frame. A facial track may be generated by grouping the faces detected and by traversing the sequence of frames forwards and backwards. Facial tracks may be joined together within a shot to generate a single track for a person's face within the shot, even when the tracks are discontinuous.

公开(公告)号：EP2543001A2

公开(公告)日：2013-01-09

申请号：EP11751117.0

申请日：2011-02-25

Applicant: Microsoft Corporation

Inventor： KRUPKA, Eyal ,  ABRAMOVSKI, Igor ,  KVIATKOVSKY, Igor

IPC: G06K9/20

CPC classification number: G06K9/6218 ,  G06F17/30259 ,  G06K9/00288 ,  G06K9/00677 ,  G06K9/623 ,  G06K2009/00328 ,  G06K2209/27

Abstract: A user's collection of images may be analyzed to identify people's faces within the images, then create clusters of similar faces, where each of the clusters may represent a person. The clusters may be ranked in order of size to determine a relative importance of the associated person to the user. The ranking may be used in many social networking applications to filter and present content that may be of interest to the user. In one use scenario, the clusters may be used to identify images from a second user's image collection, where the identified images may be pertinent or interesting to the first user. The ranking may also be a function of user interactions with the images, as well as other input not related to the images. The ranking may be incrementally updated when new images are added to the user's collection.