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公开(公告)号：US09773192B2
公开(公告)日：2017-09-26
申请号：US14732738
申请日：2015-06-07
Applicant: Apple Inc.
Inventor： Xiaoxing Li , Geoffrey T. Anneheim , Jianping Zhou , Richard D. Seely , Marco Zuliani
CPC classification number: G06K9/6202 , G06T3/40 , G06T7/13 , G06T7/248 , G06T7/90 , G06T2207/10016 , G06T2207/10024
Abstract: Techniques to identify and track a pre-identified region-of-interest (ROI) through a temporal sequence of frames/images are described. In general, a down-sampled color gradient (edge map) of an arbitrary sized ROI from a prior frame may be used to generate a small template. This initial template may be used to identify a region of a new or current frame that may be overscan and used to create a current frame's edge map. By comparing the prior frame's template to the current frame's edge map, a cost value or image may be found and used to identify the current frame's ROI center. The size of the current frame's ROI may be found by varying the size of putative new ROIs and testing for their congruence with the prior frame's template. Subsequent ROI's for subsequent frames may be identified to, effectively, track an arbitrarily sized ROI through a sequence of video frames.
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公开(公告)号：US20160358341A1
公开(公告)日：2016-12-08
申请号：US14732738
申请日：2015-06-07
Applicant: Apple Inc.
Inventor： Xiaoxing Li , Geoffrey T. Anneheim , Jianping Zhou , Richard D. Seely , Marco Zuliani
CPC classification number: G06K9/6202 , G06T3/40 , G06T7/13 , G06T7/248 , G06T7/90 , G06T2207/10016 , G06T2207/10024
Abstract: Techniques to identify and track a pre-identified region-of-interest (ROI) through a temporal sequence of frames/images are described. In general, a down-sampled color gradient (edge map) of an arbitrary sized ROI from a prior frame may be used to generate a small template. This initial template may be used to identify a region of a new or current frame that may be overscan and used to create a current frame's edge map. By comparing the prior frame's template to the current frame's edge map, a cost value or image may be found and used to identify the current frame's ROI center. The size of the current frame's ROI may be found by varying the size of putative new ROIs and testing for their congruence with the prior frame's template. Subsequent ROI's for subsequent frames may be identified to, effectively, track an arbitrarily sized ROI through a sequence of video frames.
Abstract translation: 描述了通过帧/图像的时间序列来识别和跟踪预先识别的感兴趣区域（ROI）的技术。 通常，可以使用来自先前帧的任意大小的ROI的下采样颜色梯度（边缘图）来生成小模板。 该初始模板可用于识别可能被过扫描并用于创建当前帧的边缘图的新的或当前帧的区域。 通过将先前帧的模板与当前帧的边缘图进行比较，可以找到成本值或图像，并用于识别当前帧的ROI中心。 当前框架的投资回报率的大小可以通过改变推定的新投资回报率的大小和测试与先前框架模板的一致性来确定。 可以通过一系列视频帧来识别后续帧的后续ROI，以有效地跟踪任意大小的ROI。
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公开(公告)号：US20150350544A1
公开(公告)日：2015-12-03
申请号：US14292547
申请日：2014-05-30
Applicant: Apple Inc.
Inventor： George E. Williams , Geoffrey T. Anneheim
CPC classification number: H04N5/23245 , H04N1/2133 , H04N5/23232 , H04N5/2353 , H04N5/2356 , H04N5/262 , H04N5/265 , H04N19/90
Abstract: Techniques and devices for acquiring and processing timelapse video are described. The techniques use exposure bracketing to provide a plurality of images at each acquisition time. Images of the plurality are selected to minimize flicker in a timelapse video encoded from the selected images.
Abstract translation: 描述用于获取和处理时间转换视频的技术和设备。 这些技术使用曝光包围来在每个采集时间提供多个图像。 选择多个图像以最小化从所选择的图像编码的时间转换视频中的闪烁。
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公开(公告)号：US10410327B2
公开(公告)日：2019-09-10
申请号：US15990154
申请日：2018-05-25
Applicant: Apple Inc.
Inventor： Richard D. Seely , Michael W. Tao , Alexander Lindskog , Geoffrey T. Anneheim
Abstract: This disclosure relates to techniques for synthesizing out of focus effects in digital images. Digital single-lens reflex (DSLR) cameras and other cameras having wide aperture lenses typically capture images with a shallow depth of field (SDOF). SDOF photography is often used in portrait photography, since it emphasizes the subject, while deemphasizing the background via blurring. Simulating this kind of blurring using a large depth of field (LDOF) camera may require a large amount of computational resources, i.e., in order to simulate the physical effects of using a wide aperture lens while constructing a synthetic SDOF image. However, cameras having smaller lens apertures, such as mobile phones, may not have the processing power to simulate the spreading of all background light sources in a reasonable amount of time. Thus, described herein are techniques to synthesize out-of-focus background blurring effects in a computationally-efficient manner for images captured by LDOF cameras.
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公开(公告)号：US20180350043A1
公开(公告)日：2018-12-06
申请号：US15990154
申请日：2018-05-25
Applicant: Apple Inc.
Inventor： Richard D. Seely , Michael W. Tao , Alexander Lindskog , Geoffrey T. Anneheim
CPC classification number: G06T5/002 , G06T5/50 , G06T7/90 , G06T2207/10024 , H04N5/23216 , H04N5/23229
Abstract: This disclosure relates to techniques for synthesizing out of focus effects in digital images. Digital single-lens reflex (DSLR) cameras and other cameras having wide aperture lenses typically capture images with a shallow depth of field (SDOF). SDOF photography is often used in portrait photography, since it emphasizes the subject, while deemphasizing the background via blurring. Simulating this kind of blurring using a large depth of field (LDOF) camera may require a large amount of computational resources, i.e., in order to simulate the physical effects of using a wide aperture lens while constructing a synthetic SDOF image. However, cameras having smaller lens apertures, such as mobile phones, may not have the processing power to simulate the spreading of all background light sources in a reasonable amount of time. Thus, described herein are techniques to synthesize out-of-focus background blurring effects in a computationally-efficient manner for images captured by LDOF cameras.
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Patent Agency Ranking
公开(公告)号：US10909706B1
公开(公告)日：2021-02-02
申请号：US15996363
申请日：2018-06-01
Applicant: Apple Inc.
Inventor： Geoffrey T. Anneheim , Bruno J. Conejo , Stephane S. Ben Soussan , Michael W. Tao
Abstract: Determining disparity includes obtaining a first image of a scene and a second image of a scene, determining correspondences between one or more pixels of the first image and one or more pixels of the second image, performing local denoising on the correspondences based on at least on a strength and direction of gradient values for the one or more pixels of the first image and the one or more pixels of the second image, and generating a disparity map based on the determined correspondences and local denoising.
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公开(公告)号：US10755426B2
公开(公告)日：2020-08-25
申请号：US15987834
申请日：2018-05-23
Applicant: Apple Inc.
Inventor： Mark Norman Lester Jouppi , Michael Wish Tao , Eric Bujold , Stephane Simon Rene Ben Soussan , Volker Roelke , Geoffrey T. Anneheim , Julio Cesar Hernandez Zaragoza , Florian Ciurea
Abstract: An electronic device comprises circuitry implementing a depth map enhancer. The depth map enhancer obtains an initial depth map corresponding to a scene and an image of the scene. The depth map enhancer generates a refined depth map corresponding to the scene using an optimizer, the initial depth map and the image. The refined depth map includes estimated depth indicators corresponding to at least a first depth-information region, identified based at least in part on a first criterion, of the initial depth map. Input based on the refined depth map is provided to an image processing application.
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公开(公告)号：US20190362511A1
公开(公告)日：2019-11-28
申请号：US15987834
申请日：2018-05-23
Applicant: Apple Inc.
Inventor： Mark Norman Lester Jouppi , Michael Wish Tao , Eric Bujold , Stephane Simon Rene Ben Soussan , Volker Roelke , Geoffrey T. Anneheim , Julio Cesar Hernandez Zaragoza , Florian Ciurea
Abstract: An electronic device comprises circuitry implementing a depth map enhancer. The depth map enhancer obtains an initial depth map corresponding to a scene and an image of the scene. The depth map enhancer generates a refined depth map corresponding to the scene using an optimizer, the initial depth map and the image. The refined depth map includes estimated depth indicators corresponding to at least a first depth-information region, identified based at least in part on a first criterion, of the initial depth map. Input based on the refined depth map is provided to an image processing application.
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公开(公告)号：US09911061B2
公开(公告)日：2018-03-06
申请号：US14869732
申请日：2015-09-29
Applicant: Apple Inc.
Inventor： Jianping Zhou , Geoffrey T. Anneheim , Xiaoxing Li , Benjamin M. Olson
CPC classification number: G06K9/52 , G06K9/3233 , G06K9/4642 , G06K9/4661 , G06K9/4671 , G06K2009/4666 , G06T7/248 , G06T2207/10016
Abstract: Systems, methods, and computer readable media to rapidly identify and track an arbitrary sized object through a temporal sequence of frames is described. The object being tracked may initially be identified via a specified or otherwise known region-of-interest (ROI). A portion of that ROI can be used to generate an initial or reference histogram and luminosity measure, metrics that may be used to identify the ROI in a subsequent frame. For a frame subsequent to the initial or reference frame, a series of putative ROIs (each having its own location and size) may be identified and the “best” of the identified ROIs selected. As used here, the term “best” simply means that the more similar two frames' histograms and luminosity measures are, the better one is with respect to the other.
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公开(公告)号：US20160358340A1
公开(公告)日：2016-12-08
申请号：US14869732
申请日：2015-09-29
Applicant: Apple Inc.
Inventor： Jianping Zhou , Geoffrey T. Anneheim , Xiaoxing Li , Benjamin M. Olson
CPC classification number: G06K9/52 , G06K9/3233 , G06K9/4642 , G06K9/4661 , G06K9/4671 , G06K2009/4666 , G06T7/248 , G06T2207/10016
Abstract: Systems, methods, and computer readable media to rapidly identify and track an arbitrary sized object through a temporal sequence of frames is described. The object being tracked may initially be identified via a specified or otherwise known region-of-interest (ROI). A portion of that ROI can be used to generate an initial or reference histogram and luminosity measure, metrics that may be used to identify the ROI in a subsequent frame. For a frame subsequent to the initial or reference frame, a series of putative ROIs (each having its own location and size) may be identified and the “best” of the identified ROIs selected. As used here, the term “best” simply means that the more similar two frames' histograms and luminosity measures are, the better one is with respect to the other.
Abstract translation: 描述了通过帧的时间序列快速识别和跟踪任意大小的对象的系统，方法和计算机可读介质。 被跟踪的对象最初可以通过指定的或其他已知的感兴趣区域（ROI）来识别。 该ROI的一部分可用于生成初始或参考直方图和亮度度量，可用于识别后续帧中的ROI的度量。 对于初始或参考帧之后的帧，可以识别一系列推定的ROI（每个具有其自己的位置和大小），并且选择所识别的ROI的“最佳”。 如这里所使用的，术语“最佳”仅仅意味着更相似的两帧的直方图和亮度度量是相对于另一个更好的。
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