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91.发明授权Methods and apparatus for interfacing panoramic image stitching with post-processors 有权用于将全景图像拼接与后处理器进行接口的方法和装置公开(公告)号：US09135678B2
公开(公告)日：2015-09-15
申请号：US13677016
申请日：2012-11-14
Applicant: Adobe Systems Incorporated
Inventor： Dong Feng , Jen-Chan Chien , Hailin Jin
CPC classification number: G06T3/4038 , G06T3/0062 , G06T5/006 , G06T2200/21 , G06T2200/32
Abstract: Methods and apparatus for describing a projection model, used by a panoramic image stitching module to generate panoramic images and for communicating the projection model to other processes. A post-processing module may access and use the projection model provided by the panoramic image stitching module to perform one or more post-processing methods on the panoramic image, rather than requiring the user to input the projection model via a user interface or requiring the post-processing module to estimate the projection model according to a mathematical analysis of the panoramic image.
Abstract translation: 用于描述投影模型的方法和装置，由全景图像拼接模块用于生成全景图像并将投影模型传达给其他过程。 后处理模块可以访问和使用由全景图像拼接模块提供的投影模型来对全景图像执行一个或多个后处理方法，而不是要求用户经由用户界面输入投影模型或要求 后处理模块根据全景图像的数学分析来估计投影模型。
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公开(公告)号：US09129399B2
公开(公告)日：2015-09-08
申请号：US13794300
申请日：2013-03-11
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Zhuoyuan Chen , Zhe Lin , Scott D. Cohen
CPC classification number: G06T7/204 , G06T7/215 , G06T7/223 , G06T7/248 , G06T7/337 , G06T2207/20016 , G06T2207/20021
Abstract: In embodiments of optical flow with nearest neighbor field fusion, an initial motion field can be generated based on the apparent motion of objects between digital images, and the initial motion field accounts for small displacements of the object motion. Matching patches of a nearest neighbor field can also be determined for the digital images, where patches of an initial size are compared to determine the matching patches, and the nearest neighbor field accounts for large displacements of the object motion. Additionally, region patch matches can be compared and determined between the digital images, where the region patches are larger than the initial size matching patches. Optimal pixel assignments can then be determined for a fused image representation of the digital images, where the optimal pixel assignments are determined from the initial motion field, the matching patches, and the region patch matches.
Abstract translation: 在具有最近邻场融合的光流的实施例中，可以基于数字图像之间的物体的明显运动来生成初始运动场，并且初始运动场考虑到物体运动的小位移。 还可以为数字图像确定最近邻域的匹配补丁，其中比较初始大小的补丁以确定匹配补丁，并且最近邻域考虑对象运动的大位移。 另外，可以在数字图像之间比较和确定区域补丁匹配，其中区域补丁大于初始大小匹配补丁。 然后可以确定数字图像的融合图像表示的最佳像素分配，其中从初始运动场，匹配补丁和区域补丁匹配确定最佳像素分配。
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公开(公告)号：US09053392B2
公开(公告)日：2015-06-09
申请号：US14012770
申请日：2013-08-28
Applicant: Adobe Systems Incorporated
Inventor： Jianchao Yang , Guang Chen , Hailin Jin , Jonathan Brandt , Elya Shechtman
CPC classification number: G06K9/6267 , G06K9/00979 , G06K9/4671 , G06K9/6219 , G06K9/6298 , G06K9/6828
Abstract: A hierarchy machine may be configured as a clustering machine that utilizes local feature embedding to organize visual patterns into nodes that each represent one or more visual patterns. These nodes may be arranged as a hierarchy in which a node may have a parent-child relationship with one or more other nodes. The hierarchy machine may implement a node splitting and tree-learning algorithm that includes hard-splitting of nodes and soft-assignment of nodes to perform error-bounded splitting of nodes into clusters. This may enable the hierarchy machine, which may form all or part of a visual pattern recognition system, to perform large-scale visual pattern recognition, such as font recognition or facial recognition, based on a learned error-bounded tree of visual patterns.
Abstract translation: 层次机器可以被配置为利用局部特征嵌入将可视图案组织成每个表示一个或多个视觉图案的节点的聚类机器。 这些节点可以被布置为其中节点可以与一个或多个其他节点具有父子关系的层级。 层次机器可以实现节点分割和树学习算法，其包括节点的硬分割和节点的软分配，以执行节点到分簇的有界限制的分割。 这可以使得可以形成视觉图案识别系统的全部或一部分的层次机器基于学习的有界错误的视觉图案树来执行诸如字体识别或面部识别的大规模视觉模式识别。
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公开(公告)号：US20150131915A1
公开(公告)日：2015-05-14
申请号：US14080659
申请日：2013-11-14
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jianchao Yang , Hailin Jin , Xin Lu
CPC classification number: G06T5/002 , G06K9/4609 , G06K9/4642 , G06K9/56 , G06T5/50 , G06T2207/20012 , G06T2207/20021 , G06T2207/20182
Abstract: In techniques for adaptive denoising with internal and external patches, example image patches taken from example images are grouped into partitions of similar patches, and a partition center patch is determined for each of the partitions. An image denoising technique is applied to image patches of a noisy image to generate modified image patches, and a closest partition center patch to each of the modified image patches is determined. The image patches of the noisy image are then classified as either a common patch or a complex patch of the noisy image, where an image patch is classified based on a distance between the corresponding modified image patch and the closest partition center patch. A denoising operator can be applied to an image patch based on the classification, such as applying respective denoising operators to denoise the image patches that are classified as the common patches of the noisy image.
Abstract translation: 在使用内部和外部补丁进行自适应去噪的技术中，从示例图像获取的示例图像修补程序分组到类似修补程序的分区中，并为每个分区确定分区中心修补程序。 将图像去噪技术应用于噪声图像的图像补丁以产生修改后的图像斑块，并确定每个修改后的图像斑块的最接近的分割中心斑块。 然后，噪声图像的图像块被分类为噪声图像的公共补丁或复杂补丁，其中基于对应的修改的图像补丁和最接近的分割中心补丁之间的距离对图像补丁进行分类。 可以基于分类将去噪算子应用于图像补片，例如应用相应的去噪算子去除被分类为噪声图像的公共斑块的图像斑块。
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公开(公告)号：US20150110386A1
公开(公告)日：2015-04-23
申请号：US14060076
申请日：2013-10-22
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Hailin Jin
CPC classification number: G06T5/002 , G06T2207/20021
Abstract: Image denoising techniques are described. In one or more implementations, a denoising result is computed by a computing device for a patch of an image. One or more partitions are located by the computing device that correspond to the denoising result and a denoising operator is obtained by the computing device that corresponds to the located one or more partitions. The obtained denoising operator is applied by the computing device to the image.
Abstract translation: 描述了图像去噪技术。 在一个或多个实现中，由计算设备计算图像块的去噪结果。 一个或多个分区由计算设备定位，其对应于去噪结果，并且由与所定位的一个或多个分区相对应的计算设备获得去噪算子。 所获得的去噪算子由计算装置应用于图像。
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Patent Agency Ranking
公开(公告)号：US20140254882A1
公开(公告)日：2014-09-11
申请号：US13794300
申请日：2013-03-11
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Hailin Jin , Zhuoyuan Chen , Zhe Lin , Scott D. Cohen
IPC: G06K9/46
CPC classification number: G06T7/204 , G06T7/215 , G06T7/223 , G06T7/248 , G06T7/337 , G06T2207/20016 , G06T2207/20021
Abstract: In embodiments of optical flow with nearest neighbor field fusion, an initial motion field can be generated based on the apparent motion of objects between digital images, and the initial motion field accounts for small displacements of the object motion. Matching patches of a nearest neighbor field can also be determined for the digital images, where patches of an initial size are compared to determine the matching patches, and the nearest neighbor field accounts for large displacements of the object motion. Additionally, region patch matches can be compared and determined between the digital images, where the region patches are larger than the initial size matching patches. Optimal pixel assignments can then be determined for a fused image representation of the digital images, where the optimal pixel assignments are determined from the initial motion field, the matching patches, and the region patch matches.
Abstract translation: 在具有最近邻场融合的光流的实施例中，可以基于数字图像之间的物体的明显运动来生成初始运动场，并且初始运动场考虑到物体运动的小位移。 还可以为数字图像确定最近邻域的匹配补丁，其中比较初始大小的补丁以确定匹配补丁，并且最近邻域考虑对象运动的大位移。 另外，可以在数字图像之间比较和确定区域补丁匹配，其中区域补丁大于初始大小匹配补丁。 然后可以确定数字图像的融合图像表示的最佳像素分配，其中从初始运动场，匹配补丁和区域补丁匹配确定最佳像素分配。
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公开(公告)号：US08830347B2
公开(公告)日：2014-09-09
申请号：US13757518
申请日：2013-02-01
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin
CPC classification number: G06K9/3275 , H04N5/23238 , H04N5/247 , H04N5/3572
Abstract: A method for aligning and unwarping distorted images in which lens profiles for a variety of lens and camera combinations are precomputed. Metadata stored with images is used to automatically determine if a set of component images include an excessive amount of distortion, and if so the metadata is used to determine an appropriate lens profile and initial unwarping function. The initial unwarping function is applied to the coordinates of feature points of the component images to generate substantially rectilinear feature points, which are used to estimate focal lengths, centers, and relative rotations for pairs of the images. A global nonlinear optimization is applied to the initial unwarping function(s) and the relative rotations to generate optimized unwarping functions and rotations for the component images. The optimized unwarping functions and rotations may be used to render a panoramic image.
Abstract translation: 一种用于对准和扭曲失真图像的方法，其中预先计算用于各种镜头和相机组合的透镜轮廓。 使用存储有图像的元数据来自动确定一组分量图像是否包含过多的失真，如果是，则使用元数据来确定适当的透镜轮廓和初始不正确的功能。 将初始不正确函数应用于分量图像的特征点的坐标，以生成基本上直线的特征点，其用于估计图像对的焦距，中心和相对旋转。 全局非线性优化被应用于初始不平衡函数和相对旋转以产生用于分量图像的优化的不正确函数和旋转。 优化的不正确功能和旋转可用于渲染全景图像。
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公开(公告)号：US10216766B2
公开(公告)日：2019-02-26
申请号：US15463769
申请日：2017-03-20
Applicant: ADOBE SYSTEMS INCORPORATED
Inventor： Zhe Lin , Xiaohui Shen , Jianming Zhang , Hailin Jin , Yingwei Li
Abstract: A framework is provided for associating images with topics utilizing embedding learning. The framework is trained utilizing images, each having multiple visual characteristics and multiple keyword tags associated therewith. Visual features are computed from the visual characteristics utilizing a convolutional neural network and an image feature vector is generated therefrom. The keyword tags are utilized to generate a weighted word vector (or “soft topic feature vector”) for each image by calculating a weighted average of word vector representations that represent the keyword tags associated with the image. The image feature vector and the soft topic feature vector are aligned in a common embedding space and a relevancy score is computed for each of the keyword tags. Once trained, the framework can automatically tag images and a text-based search engine can rank image relevance with respect to queried keywords based upon predicted relevancy scores.
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公开(公告)号：US20180357519A1
公开(公告)日：2018-12-13
申请号：US15616776
申请日：2017-06-07
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , John Philip Collomosse
CPC classification number: G06K9/6282 , G06K9/6255 , G06K9/6256 , G06K9/6262 , G06K9/726
Abstract: A combined structure and style network is described. Initially, a large set of training images, having a variety of different styles, is obtained. Each of these training images is associated with one of multiple different predetermined style categories indicating the image's style and one of multiple different predetermined semantic categories indicating objects depicted in the image. Groups of these images are formed, such that each group includes an anchor image having one of the styles, a positive-style example image having the same style as the anchor image, and a negative-style example image having a different style. Based on those groups, an image style network is generated to identify images having desired styling by recognizing visual characteristics of the different styles. The image style network is further combined, according to a unifying training technique, with an image structure network configured to recognize desired objects in images irrespective of image style.
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100.发明申请公开(公告)号：US20180143988A1
公开(公告)日：2018-05-24
申请号：US15357864
申请日：2016-11-21
Applicant: Adobe Systems Incorporated
Inventor： Matthew Douglas Hoffman , Longqi Yang , Hailin Jin , Chen Fang
IPC: G06F17/30
Abstract: A digital medium environment includes an asset processing application that performs editing of assets. A projection function is trained using pairs of actions pertaining to software edits, and assets resulting from the actions to learn a joint embedding between the actions and the assets. The projection function is used in the asset processing application to recommend software actions to create an asset, and also to recommend assets to demonstrate the effects of software actions. Recommendations are based on ranking distance measures that measure distances between actions representations and asset representations in a vector space.
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