Fast Template-Based Tracking
    21.
    发明申请
    Fast Template-Based Tracking 有权
    快速的基于模板的跟踪

    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.

    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。

    Methods of image fusion for image stabilization
    22.
    发明授权
    Methods of image fusion for image stabilization 有权
    用于图像稳定的图像融合方法

    公开(公告)号:US09262684B2

    公开(公告)日:2016-02-16

    申请号:US13911740

    申请日:2013-06-06

    Applicant: Apple Inc.

    Abstract: Systems, methods, and computer readable media to improve image stabilization operations are described. Novel approaches for fusing non-reference images with a pre-selected reference frame in a set of commonly captured images are disclosed. The fusing approach may use a soft transition by using a weighted average for ghost/non-ghost pixels to avoid sudden transition between neighborhood and almost similar pixels. Additionally, the ghost/non-ghost decision can be made based on a set of neighboring pixels rather than independently for each pixel. An alternative approach may involve performing a multi-resolution decomposition of all the captured images, using temporal fusion, spatio-temporal fusion, or combinations thereof, at each level and combining the different levels to generate an output image.

    Abstract translation: 描述了用于改善图像稳定操作的系统,方法和计算机可读介质。 公开了一组用于将非参考图像与一组普通捕获图像中的预选参考帧融合的新方法。 融合方法可以通过使用重影/非重像素的加权平均值来使用软转换,以避免邻域和几乎相似像素之间的突然过渡。 此外,可以基于一组相邻像素而不是针对每个像素独立地进行重影/非重影决定。 替代方法可以包括在每个级别上使用时间融合,时空融合或其组合执行所有捕获图像的多分辨率分解,并组合不同的级别以生成输出图像。

    VIDEO ROLLING SHUTTER CORRECTION FOR LENS MOVEMENT IN OPTICAL IMAGE STABILIZATION CAMERAS
    23.
    发明申请
    VIDEO ROLLING SHUTTER CORRECTION FOR LENS MOVEMENT IN OPTICAL IMAGE STABILIZATION CAMERAS 有权
    光学图像稳定摄像机镜头运动的视频滚动快门校正

    公开(公告)号:US20150350550A1

    公开(公告)日:2015-12-03

    申请号:US14547107

    申请日:2014-11-18

    Applicant: Apple Inc.

    Abstract: In some embodiments, a method for compensating for lens motion includes estimating a starting position of a lens assembly associated with captured pixel data. The captured pixel data is captured from an image sensor. In some embodiments, the method further includes calculating from the starting position and position data received from the one or more position sensors lens movement associated with the captured pixel data. The lens movement is mapped into pixel movement associated with the captured pixel data. A transform matrix is adjusted to reflect at least the pixel movement. A limit factor associated with the position data is calculated. The captured pixel data is recalculated using the transform matrix and the limit factor.

    Abstract translation: 在一些实施例中,用于补偿透镜运动的方法包括估计与捕获的像素数据相关联的透镜组件的起始位置。 从图像传感器捕获捕获的像素数据。 在一些实施例中,该方法还包括从与所捕获的像素数据相关联的一个或多个位置传感器透镜运动接收到的起始位置和位置数据进行计算。 透镜移动被映射到与捕获的像素数据相关联的像素运动。 调整变换矩阵以至少反映像素移动。 计算与位置数据相关联的极限因子。 使用变换矩阵和极限因子重新计算捕获的像素数据。

    Noise reduction based on motion sensors
    24.
    发明授权
    Noise reduction based on motion sensors 有权
    基于运动传感器的降噪

    公开(公告)号:US08928765B2

    公开(公告)日:2015-01-06

    申请号:US13630961

    申请日:2012-09-28

    Applicant: Apple Inc.

    Inventor: Jianping Zhou

    CPC classification number: H04N5/23254 H04N5/217 H04N5/23258 H04N5/23267

    Abstract: A method for reducing noise in a sequence of frames may include generating a transformed frame from an input frame according to a perspective transform of a transform matrix, wherein the transform matrix corrects for motion associated with input frame. A determination may be made to identify pixels in the transformed frame that have a difference with corresponding pixels in a neighboring frame below a threshold. An output frame may be generated by adjusting pixels in the transformed frame that are identified to have the difference with the corresponding pixels in the neighboring frame below the threshold.

    Abstract translation: 用于减少帧序列中的噪声的方法可以包括根据变换矩阵的透视变换从输入帧生成变换帧,其中变换矩阵校正与输入帧相关联的运动。 可以确定识别与低于阈值的相邻帧中的相应像素有差异的变换帧中的像素。 可以通过调整被识别为与阈值以下的相邻帧中的相应像素具有差异的变换帧中的像素来生成输出帧。

    Reference Frame Selection for Still Image Stabilization
    25.
    发明申请
    Reference Frame Selection for Still Image Stabilization 有权
    静态图像稳定的参考帧选择

    公开(公告)号:US20140362256A1

    公开(公告)日:2014-12-11

    申请号:US13911873

    申请日:2013-06-06

    Applicant: Apple Inc.

    CPC classification number: H04N5/23277

    Abstract: Systems, methods, and computer readable media to improve image stabilization operations are described. A novel combination of image quality and commonality metrics are used to identify a reference frame from a set of commonly captured images which, when the set's other images are combined with it, results in a quality stabilized image. The disclosed image quality and commonality metrics may also be used to optimize the use of a limited amount of image buffer memory during image capture sequences that return more images that the memory may accommodate at one time. Image quality and commonality metrics may also be used to effect the combination of multiple relatively long-exposure images which, when combined with a one or more final (relatively) short-exposure images, yields images exhibiting motion-induced blurring in interesting and visually pleasing ways.

    Abstract translation: 描述了用于改善图像稳定操作的系统,方法和计算机可读介质。 使用图像质量和共性度量的新颖组合来从一组共同拍摄的图像中识别参考帧,当集合的其他图像与其组合时,其导致质量稳定的图像。 公开的图像质量和通用性度量还可以用于在图像捕获序列期间优化使用有限量的图像缓冲存储器,从而可以一次返回存储器可以容纳的更多图像。 图像质量和共性度量也可用于影响多个相对较长曝光图像的组合,当与一个或多个最终(相对)短曝光图像组合时,产生显示运动诱导的模糊的图像,其在有趣和视觉上令人满意 方法。

    Efficient unwanted reflection artifact mitigation in videos for embedded devices

    公开(公告)号:US12177567B2

    公开(公告)日:2024-12-24

    申请号:US17805399

    申请日:2022-06-03

    Applicant: Apple Inc.

    Abstract: Devices, methods, and non-transitory computer readable media are disclosed herein to repair or mitigate the appearance of unwanted reflection artifacts in captured video image streams. These unwanted reflection artifacts often present themselves as brightly-colored spots, circles, rings, or halos that reflect the shape of a bright light source in the captured image. These artifacts, also referred to herein as “ghosts” or “green ghosts” (due to often having a greenish tint), are typically located in regions of the captured images where there is not actually a bright light source located in the image. In fact, such unwanted reflection artifacts often present themselves on the image sensor across the principal point of the lens from where the actual bright light source in the captured image is located. Such devices, methods and computer readable media may be configured to detect, track, and repair such unwanted reflection artifacts in an intelligent and efficient fashion.

    Systems and methods for multi-sensor image enhancement

    公开(公告)号:US11688100B1

    公开(公告)日:2023-06-27

    申请号:US17351869

    申请日:2021-06-18

    Applicant: Apple Inc.

    CPC classification number: G06T7/80 G06N3/04 G06T9/002 H04N23/62

    Abstract: Devices, methods, and non-transitory program storage devices are disclosed to provide enhanced images in multi-camera systems, e.g., by using information from images captured by cameras with different properties in terms of optics and/or sensors. In one embodiment, the techniques comprise: obtaining a first image from a first image capture device, wherein the first image has a first field of view (FOV) and a first set of quality characteristics; obtaining a second image from a second image capture device, wherein the second image has a second FOV and a second set of quality characteristics, and wherein the second FOV partially overlaps the first FOV; obtaining a neural network that produces a modified second image having a modified second set of quality characteristics determined by the neural network attempting to match the first set of quality characteristics; and generating an output image based, at least in part, on the modified second image.

    Seamless preview stitching for multiple cameras

    公开(公告)号:US11276145B2

    公开(公告)日:2022-03-15

    申请号:US16835551

    申请日:2020-03-31

    Applicant: Apple Inc.

    Abstract: Systems and methods for stitching videos are disclosed. Image-based registration between frames from a first video source and frames from a second video source is performed at a first rate. Calibration-based registration between frames from the first video source and frames from the second video source are performed at a second rate higher than the first rate. Then, for a first frame from the first video source for which calibration-based registration data and image-based registration data have been generated, a stitching transform that maps the first frame to a counterpart frame from the second video source based on image-based registration data is generated. A delta transform from the image-based registration data and the calibration-based registration data at the first frame is also derived. For a subsequent frame from the first video source for which calibration-based registration data have been generated, but no image-based registration data have been generated, a stitching transform that maps the subsequent frame to a counterpart frame from the second video source based on the calibration-based registration data and the delta transform is generated. Frames from the first video source and frames from the second video source are stitched according to their respective generated stitching transforms.

    Switchover control techniques for dual-sensor camera system

    公开(公告)号:US10701256B2

    公开(公告)日:2020-06-30

    申请号:US15617918

    申请日:2017-06-08

    Applicant: Apple Inc.

    Abstract: Techniques are described for automatically selecting between multiple image capture subsystems with overlapping fields of view but different optical properties. A selection may be made by estimating a plurality of operational characteristics of an image capture event, and, based on those estimates, selecting a primary image capture subsystem for the image capture event. For example, in a device such as a cellphone comprising two capture subsystems, each subsystem including a lens system and sensor system where each subsystem has a different fixed optical zoom parameter, a subsystem can be chosen based on a combination of desired zoom value, estimated focus distance, and estimated scene brightness.

    Fast histogram-based object tracking

    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.

    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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