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公开(公告)号：US20150156419A1
公开(公告)日：2015-06-04
申请号：US14094010
申请日：2013-12-02
Applicant: YAHOO! INC.
Inventor： Gaurav Aggarwal , Nikhil Rasiwasia , Kshitiz Garg , Vijay Mahadevan
CPC classification number: H04N5/23293 , G06T5/003 , G06T7/0002 , G06T2207/20201 , G06T2207/30168 , H04N5/23222 , H04N5/23251 , H04N5/23254 , H04N5/23258 , H04N5/357
Abstract: Users are provided with feedback regarding blurriness of an image in real-time. When an image is received, a blur score is automatically generated in addition to a visual that indicates the extent of blurriness across the picture. The blur score is calculated by aggregating an image_blur_score and optionally a motion_blur_score. A user can also be provided with suggestions on improving image sharpness and help in determining if another image needs to be taken.
Abstract translation: 向用户提供关于图像实时模糊的反馈。 当接收图像时，除了指示整个图片的模糊程度的视觉外，还自动生成模糊分数。 通过聚合image_blur_score和可选的motion_blur_score来计算模糊分数。 还可以向用户提供改进图像清晰度的建议，并帮助确定是否需要另外的图像。
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公开(公告)号：US20180005088A1
公开(公告)日：2018-01-04
申请号：US15198295
申请日：2016-06-30
Applicant: Yahoo! Inc.
Inventor： Sachin Sudhakar Farfade , Vijay Mahadevan , Ayman Kaheel , Ayyappan Arasu , Venkat Kumar Reddy Barakam , Jan Kiran Mahadeokar
CPC classification number: G06K9/6297 , G06F17/30259 , G06K9/00228 , G06K9/036 , G06K9/481 , G06K9/6224
Abstract: Disclosed are systems and methods for automatic selection of canonical digital images from a large corpus of digital images, such as the corpus of digital images available on the web, for an entity, such as and without limitation a person, a point of interest, object, etc. The automated, unsupervised approach for selecting a diverse set of high quality, canonical digital images, is well suited for processing a large corpus of digital images. A set of canonical digital images identified for an entity can be retrieved in response to a digital image request for digital images depicting the entity.
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公开(公告)号：US09210327B2
公开(公告)日：2015-12-08
申请号：US14094010
申请日：2013-12-02
Applicant: Yahoo! Inc.
Inventor： Gaurav Aggarwal , Nikhil Rasiwasia , Kshitiz Garg , Vijay Mahadevan
CPC classification number: H04N5/23293 , G06T5/003 , G06T7/0002 , G06T2207/20201 , G06T2207/30168 , H04N5/23222 , H04N5/23251 , H04N5/23254 , H04N5/23258 , H04N5/357
Abstract: Users are provided with feedback regarding blurriness of an image in real-time. When an image is received, a blur score is automatically generated in addition to a visual that indicates the extent of blurriness across the picture. The blur score is calculated by aggregating an image_blur_score and optionally a motion_blur_score. A user can also be provided with suggestions on improving image sharpness and help in determining if another image needs to be taken.
Abstract translation: 向用户提供关于图像实时模糊的反馈。 当接收图像时，除了指示整个图片的模糊程度的视觉外，还自动生成模糊分数。 通过聚合image_blur_score和可选的motion_blur_score来计算模糊分数。 还可以向用户提供改进图像清晰度的建议，并帮助确定是否需要另外的图像。
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