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公开(公告)号：US11776141B1
公开(公告)日：2023-10-03
申请号：US17357401
申请日：2021-06-24
Applicant: Apple Inc.
Inventor： Gijesh Varghese , Farhan A. Baqai , Giancarlo Todone , Hao Sun , Richard D. Seely
CPC classification number: G06T7/337 , G06T3/0093 , G06T5/20 , G06T5/50 , G06T2207/20221
Abstract: Devices, methods, and non-transitory program storage devices (NPSDs) for an improved, so-called “hybrid” image registration process are disclosed herein, comprising: obtaining a first set of captured images, wherein the first set of captured images comprises a reference image and one or more bracketed images; and for each of the one or more bracketed images: performing a first (e.g., global) registration operation and a second (e.g., dense, or other localized) registration operation on the bracketed image with respect to the reference image, wherein each of the first and second registration operations produces an output; generating a blend map for the bracketed image, wherein each value in the blend map indicates whether to use the first or second registration operation output for a corresponding one or more pixels when registering the bracketed image with the reference image; and registering the bracketed image with the reference image, according to the generated blend map.
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公开(公告)号：US10992845B1
公开(公告)日：2021-04-27
申请号：US16565965
申请日：2019-09-10
Applicant: Apple Inc.
Inventor： Richard D. Seely , Shuang Gao , Alexandre Naaman , Patrick Shehane
Abstract: This disclosure relates to techniques for synthesizing out of focus blurring effects in digital images. Cameras having wide aperture lenses typically capture images with a shallow depth of field (SDOF). SDOF cameras are often used in portrait photography, since they emphasize subjects, 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., to simulate the physical effects of using a wide aperture lens, while constructing a synthetic SDOF image. Moreover, cameras having smaller lens apertures, such as those in mobile phones, may not have the ability to accurately estimate or recreate the true color of clipped background light sources. Described herein are techniques to synthesize out of focus background blurring effects that attempt to reproduce accurate light intensity and color values for clipped background light sources in images captured by LDOF cameras.
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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：US11570374B1
公开(公告)日：2023-01-31
申请号：US17357501
申请日：2021-06-24
Applicant: Apple Inc.
Inventor： Hao Sun , Farhan A. Baqai , Giancarlo Todone , Gijesh Varghese , Morten Poulsen , Richard D. Seely , Richard J. Shields , Srivani Pinneli , Wu Cheng
Abstract: Devices, methods, and computer-readable media are disclosed, describing an adaptive, subject-aware approach for image bracket selection and fusion, e.g., to generate high quality images in a wide variety of capturing conditions, including low light conditions. An incoming image stream may be obtained from an image capture device, comprising images captured using differing default exposure values, e.g., according to a predetermined pattern. When a capture request is received, it may be detected whether one or more human or animal subjects are present in the incoming image stream. If a subject is detected, an exposure time of one or more images selected from the incoming image stream may be reduced relative to its default exposure time. Prior to the fusion operation, one of the selected images may be designated a reference image for the fusion operation based, at least in part, on a sharpness score and/or a blink score of the image.
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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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Patent Agency Ranking
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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公开(公告)号：US11682108B2
公开(公告)日：2023-06-20
申请号：US17473531
申请日：2021-09-13
Applicant: Apple Inc.
Inventor： Richard D. Seely , Alexandre Naaman , Patrick Shehane , Andre Souza Dos Santos , Behkish J. Manzari
CPC classification number: G06T5/003 , G06V30/19127 , G06T2200/24
Abstract: This disclosure relates to various implementations that dynamically adjust one or more shallow depth of field (SDOF) parameters based on a designated, artificial aperture value. The implementations obtain a designated, artificial aperture value that modifies an initial aperture value for an image frame. The designated, artificial aperture value generates a determined amount of synthetically-produced blur within the image frame. The implementations determine an aperture adjustment factor based on the designated, artificial aperture value in relation to a default so-called “tuning aperture value” (for which the camera's operations may have been optimized). The implementations may then modify, based on the aperture adjustment factor, one or more SDOF parameters for an SDOF operation, which may, e.g., be configured to render a determined amount of synthetic bokeh within the image frame. In response the modified SDOF parameters, the implementations may render an updated image frame that corresponds to the designated, artificial aperture value.
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公开(公告)号：US20210407050A1
公开(公告)日：2021-12-30
申请号：US17473531
申请日：2021-09-13
Applicant: Apple Inc.
Inventor： Richard D. Seely , Alexandre Naaman , Patrick Shehane , Andre Souza Dos Santos , Behkish J. Manzari
IPC: G06T5/00
Abstract: This disclosure relates to various implementations that dynamically adjust one or more shallow depth of field (SDOF) parameters based on a designated, artificial aperture value. The implementations obtain a designated, artificial aperture value that modifies an initial aperture value for an image frame. The designated, artificial aperture value generates a determined amount of synthetically-produced blur within the image frame. The implementations determine an aperture adjustment factor based on the designated, artificial aperture value in relation to a default so-called “tuning aperture value” (for which the camera's operations may have been optimized). The implementations may then modify, based on the aperture adjustment factor, one or more SDOF parameters for an SDOF operation, which may, e.g., be configured to render a determined amount of synthetic bokeh within the image frame. In response the modified SDOF parameters, the implementations may render an updated image frame that corresponds to the designated, artificial aperture value.
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公开(公告)号：US11120528B1
公开(公告)日：2021-09-14
申请号：US16565985
申请日：2019-09-10
Applicant: Apple Inc.
Inventor： Richard D. Seely , Alexandre Naaman , Patrick Shehane , Andre Souza Dos Santos , Behkish J. Manzari
IPC: G06T5/00
Abstract: This disclosure relates to various implementations that dynamically adjust one or more shallow depth of field (SDOF) parameters based on a designated, artificial aperture value. The implementations obtain a designated, artificial aperture value that modifies an initial aperture value for an image frame. The designated, artificial aperture value generates a determined amount of synthetically-produced blur within the image frame. The implementations determine an aperture adjustment factor based on the designated, artificial aperture value in relation to a default so-called “tuning aperture value” (for which the camera's operations may have been optimized). The implementations may then modify, based on the aperture adjustment factor, one or more SDOF parameters for an SDOF operation, which may, e.g., be configured to render a determined amount of synthetic bokeh within the image frame. In response the modified SDOF parameters, the implementations may render an updated image frame that corresponds to the designated, artificial aperture value.
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公开(公告)号：US11102421B1
公开(公告)日：2021-08-24
申请号：US16996375
申请日：2020-08-18
Applicant: Apple Inc.
Inventor： Richard D. Seely , Giancarlo Todone , Hao Sun , Farhan A. Baqai
Abstract: An incoming image stream may be obtained from an image capture device operating in low-light conditions and/or a simulated long exposure image capture mode. As images are obtained, a weighting operation may be performed on the pixels of the captured images to generate and/or update an accumulative weight map, wherein the weighting is based, e.g., on the proximity of the captured pixels' values to the respective image capture device's maximum observable pixel value. As batches of images are obtained, they may be fused, e.g., according to the accumulative weight map, in a memory-efficient manner that places an upper limit on the overall memory footprint of the fusion operations, to simulate an actual long exposure image capture. In some embodiments, the weight map may be stored at a lower resolution than the obtained images and then upscaled, e.g., via the use of guided filters, before being applied in the fusion operations.
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