公开(公告)号：WO2013095727A1

公开(公告)日：2013-06-27

申请号：PCT/US2012/055447

申请日：2012-09-14

Applicant: APPLE INC. ,  SOLEM, Jan Erik ,  ROUSSON, Michael

Inventor： SOLEM, Jan Erik ,  ROUSSON, Michael

IPC: G06K9/00 ,  G06K9/62

CPC classification number: G06K9/00221 ,  G06K9/00275 ,  G06K9/621

Abstract: Systems, methods, and computer readable media for determining and applying face recognition parameter sets are described. In general, techniques are disclosed for identifying and constructing a unique combination of facial recognition discriminators into a "face feature vector" that has been found to be more robust ( e.g ., stable to image noise, a person's pose, and scene illumination) and accurate ( e.g ., provide high recognition rates) than prior art techniques. More particularly, a face feature vector may be generated by the combination of shape descriptors ( e.g ., as generated by two-dimensional and three-dimensional shape models) and texture descriptors ( e.g ., as generated by global and local texture models).

Abstract translation: 描述了用于确定和应用面部识别参数集的系统，方法和计算机可读介质。 通常，公开了用于将面部识别鉴别器的唯一组合识别和构造成已被发现更加鲁棒的“面部特征向量”的技术（例如，稳定于图像噪声，人的姿势和场景照明）和准确的 （例如，提供高识别率）比现有技术。 更具体地，可以通过形状描述符（例如，由二维和三维形状模型生成）和纹理描述符（例如，由全局和局部纹理模型生成）的组合来生成面部特征向量。

公开(公告)号：WO2015034725A1

公开(公告)日：2015-03-12

申请号：PCT/US2014/052965

申请日：2014-08-27

Applicant: APPLE INC.

Inventor： KEATING, Brett ,  WONG, Vincent ,  SACHS, Todd ,  MOLGAARD, Claus ,  ROUSSON, Michael ,  HARRIS, Elliott ,  TITI, Justin ,  HSU, Karl ,  BRASKET, Jeff ,  ZULIANI, Marco

IPC: H04N5/232 ,  H04N1/21

CPC classification number: H04N5/77 ,  G06K9/00765 ,  G06K9/46 ,  G06K9/6201 ,  G06K9/6267 ,  G06K2009/4666 ,  G06T7/11 ,  H04N5/147 ,  H04N5/23219 ,  H04N5/23222 ,  H04N5/23229 ,  H04N5/23293 ,  H04N21/8456

Abstract: Systems and methods for improving automatic selection of keeper images from a commonly captured set of images are described. A combination of image type identification and image quality metrics may be used to identify one or more images in the set as keeper images. Image type identification may be used to categorize the captured images into, for example, three or more categories. The categories may include portrait, action, or "other." Depending on the category identified, the images may be analyzed differently to identify keeper images. For portrait images, an operation may be used to identify the best set of faces. For action images, the set may be divided into sections such that keeper images selected from each section tell the story of the action. For the "other" category, the images may be analyzed such that those having higher quality metrics for an identified region of interest are selected.

Abstract translation: 描述了用于改善从一组共同拍摄的图像中保持图像的自动选择的系统和方法。 可以使用图像类型识别和图像质量度量的组合来识别该集合中的一个或多个图像作为保持器图像。 可以使用图像类型识别来将捕获的图像分类为例如三个或更多个类别。 类别可能包括纵向，动作或“其他”。 根据识别的类别，可以不同地分析图像以识别饲养员图像。 对于肖像图像，可以使用操作来识别最佳面部组。 对于动作图像，该集合可以被划分为部分，使得从每个部分中选择的守护者图像讲述动作的故事。 对于“其他”类别，可以分析图像，以便选择对于所识别的感兴趣区域具有较高质量度量的图像。

公开(公告)号：EP3044947B1

公开(公告)日：2020-09-23

申请号：EP14767189.5

申请日：2014-08-27

Applicant: Apple Inc.

Inventor： KEATING, Brett ,  WONG, Vincent ,  SACHS, Todd ,  MOLGAARD, Claus ,  ROUSSON, Michael ,  HARRIS, Elliott ,  TITI, Justin ,  HSU, Karl ,  BRASKET, Jeff ,  ZULIANI, Marco

IPC: H04N5/232 ,  H04N1/21 ,  G06T7/11

公开(公告)号：EP3044947A1

公开(公告)日：2016-07-20

申请号：EP14767189.5

申请日：2014-08-27

Applicant: Apple Inc.

Inventor： KEATING, Brett ,  WONG, Vincent ,  SACHS, Todd ,  MOLGAARD, Claus ,  ROUSSON, Michael ,  HARRIS, Elliott ,  TITI, Justin ,  HSU, Karl ,  BRASKET, Jeff ,  ZULIANI, Marco

IPC: H04N5/232 ,  H04N1/21

Abstract: Systems and methods for improving automatic selection of keeper images from a commonly captured set of images are described. A combination of image type identification and image quality metrics may be used to identify one or more images in the set as keeper images. Image type identification may be used to categorize the captured images into, for example, three or more categories. The categories may include portrait, action, or “other.” Depending on the category identified, the images may be analyzed differently to identify keeper images. For portrait images, an operation may be used to identify the best set of faces. For action images, the set may be divided into sections such that keeper images selected from each section tell the story of the action. For the “other” category, the images may be analyzed such that those having higher quality metrics for an identified region of interest are selected.

Abstract translation: 描述了一种用于改善从一组共同拍摄的图像中保持图像的自动选择的系统和方法。 可以使用图像类型识别和图像质量度量的组合来识别该集合中的一个或多个图像作为保持器图像。 图像类型识别可以用于将捕获的图像分类为例如三个或更多个类别。 类别可以包括纵向，动作或“其他”。根据所识别的类别，可以不同地分析图像以识别守护者图像。 对于肖像图像，可以使用操作来识别最佳面部组。 对于动作图像，该集合可以被划分为部分，使得从每个部分中选择的守护者图像讲述动作的故事。 对于“其他”类别，可以分析图像，以便选择对于所识别的感兴趣区域具有较高质量度量的图像。