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公开(公告)号：US20160379132A1
公开(公告)日：2016-12-29
申请号：US14748059
申请日：2015-06-23
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Chen Fang , Jianchao Yang , Zhe Lin
Abstract: The present disclosure is directed to collaborative feature learning using social media data. For example, a machine learning system may identify social media data that includes user behavioral data, which indicates user interactions with content item. Using the identified social user behavioral data, the machine learning system may determine latent representations from the content items. In some embodiments, the machine learning system may train a machine-learning model based on the latent representations. Further, the machine learning system may extract features of the content item from the trained machine-learning model.
Abstract translation: 本公开涉及使用社交媒体数据的协作特征学习。 例如，机器学习系统可以识别包括用户行为数据的社交媒体数据，其指示用户与内容项目的交互。 使用所识别的社会用户行为数据，机器学习系统可以确定来自内容项目的潜在表示。 在一些实施例中，机器学习系统可以基于潜在表示来训练机器学习模型。 此外，机器学习系统可以从训练的机器学习模型中提取内容项的特征。
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公开(公告)号：US20160104286A1
公开(公告)日：2016-04-14
申请号：US14884338
申请日：2015-10-15
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Zihan Zhou
CPC classification number: G06T7/80 , G06T7/174 , G06T7/20 , G06T2207/10016 , G06T2207/30241 , H04N13/20
Abstract: Robust techniques for self-calibration of a moving camera observing a planar scene. Plane-based self-calibration techniques may take as input the homographies between images estimated from point correspondences and provide an estimate of the focal lengths of all the cameras. A plane-based self-calibration technique may be based on the enumeration of the inherently bounded space of the focal lengths. Each sample of the search space defines a plane in the 3D space and in turn produces a tentative Euclidean reconstruction of all the cameras that is then scored. The sample with the best score is chosen and the final focal lengths and camera motions are computed. Variations on this technique handle both constant focal length cases and varying focal length cases.
Abstract translation: 用于自动校准移动摄像机观察平面场景的强大技术。 基于平面的自校准技术可以将从点对应估计的图像之间的同形作为输入，并提供所有相机的焦距的估计。 基于平面的自校准技术可以基于焦距的固有界限空间的计数。 搜索空间的每个样本在3D空间中定义一个平面，并且反过来产生所有相机的临时欧几里德重建，然后对其进行评分。 选择具有最佳分数的样本，并计算最终焦距和相机运动。 该技术的变化处理恒定焦距情况和不同焦距情况。
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63.发明授权Image classification using images with separate grayscale and color channels 有权使用具有单独灰度和颜色通道的图像的图像分类公开(公告)号：US09230192B2
公开(公告)日：2016-01-05
申请号：US14081684
申请日：2013-11-15
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Thomas Le Paine , Jianchao Yang , Zhe Lin , Jonathan W. Brandt
CPC classification number: G06K9/6267 , G06K9/46 , G06K9/4652
Abstract: Image classification techniques using images with separate grayscale and color channels are described. In one or more implementations, an image classification network includes grayscale filters and color filters which are separate from the grayscale filters. The grayscale filters are configured to extract grayscale features from a grayscale channel of an image, and the color filters are configured to extract color features from a color channel of the image. The extracted grayscale features and color features are used to identify an object in the image, and the image is classified based on the identified object.
Abstract translation: 描述使用具有单独灰度和颜色通道的图像的图像分类技术。 在一个或多个实现中，图像分类网络包括与灰阶滤波器分离的灰度滤波器和滤色器。 灰度滤波器被配置为从图像的灰度级通道提取灰度特征，并且滤色器被配置为从图像的颜色通道中提取颜色特征。 提取的灰度特征和颜色特征用于识别图像中的对象，并且基于识别的对象对图像进行分类。
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公开(公告)号：US20150332438A1
公开(公告)日：2015-11-19
申请号：US14280421
申请日：2014-05-16
Applicant: Adobe Systems Incorporated
Inventor： Zhe Lin , Jianchao Yang , Hailin Jin , Xin Lu
CPC classification number: G06T5/005 , G06K9/00664 , G06K9/6218 , G06T5/002 , G06T2207/20081 , G06T2207/20084
Abstract: Patch partition and image processing techniques are described. In one or more implementations, a system includes one or more modules implemented at least partially in hardware. The one or more modules are configured to perform operations including grouping a plurality of patches taken from a plurality of training samples of images into respective ones of a plurality of partitions, calculating an image processing operator for each of the partitions, determining distances between the plurality of partitions that describe image similarity of patches of the plurality of partitions, one to another, and configuring a database to provide the determined distance and the image processing operator to process an image in response to identification of a respective partition that corresponds to a patch taken from the image.
Abstract translation: 描述了补丁分区和图像处理技术。 在一个或多个实现中，系统包括至少部分地以硬件实现的一个或多个模块。 一个或多个模块被配置为执行操作，包括将从多个图像的训练样本获取的多个补丁分组到多个分区中的相应的分区中，为每个分区计算图像处理算子，确定多个分割之间的距离 描述多个分区的图像相似度的分区，并且配置数据库以提供所确定的距离，并且图像处理运算符响应于对应于所采取的补丁的相应分区的标识来处理图像 从图像。
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公开(公告)号：US20150249811A1
公开(公告)日：2015-09-03
申请号：US14713914
申请日：2015-05-15
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin
CPC classification number: G06T7/2033 , G06K9/3233 , G06K9/3241 , G06K9/3275 , G06K9/4652 , G06T5/001 , G06T7/246 , G06T7/579 , G06T7/70 , G06T2200/04 , G06T2207/10012 , G06T2207/10016 , G06T2207/20164 , G06T2207/30241 , G06T2207/30244 , H04N5/232 , H04N13/00 , H04N13/10 , H04N17/002
Abstract: An initialization technique is described for determining and reconstructing a set of initial keyframes covering a portion of an image sequence according to point trajectories that may, for example, be used in an adaptive reconstruction algorithm implemented by a structure from motion (SFM) technique. A goal of the initialization technique is to compute an initial reconstruction from a subset of frames in the image sequence. Two initial keyframes are selected from a set of temporally spaced keyframe candidates, the two initial keyframes are reconstructed, and then one or more additional keyframes between the two initial keyframes are selected and reconstructed. Output of the initialization technique is a set of initial keyframes and the initial reconstruction.
Abstract translation: 描述了一种初始化技术，用于根据例如在由运动结构（SFM）技术实现的自适应重构算法中使用的点轨迹来确定和重建覆盖图像序列的一部分的一组初始关键帧。 初始化技术的目标是从图像序列中的帧子集计算初始重构。 从一组时间间隔的关键帧候选中选择两个初始关键帧，重建两个初始关键帧，然后选择和重建两个初始关键帧之间的一个或多个附加关键帧。 初始化技术的输出是一组初始关键帧和初始重构。
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Patent Agency Ranking
公开(公告)号：US09031345B2
公开(公告)日：2015-05-12
申请号：US13794408
申请日：2013-03-11
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin , Zhuoyuan Chen , Zhe Lin , Scott D. Cohen
CPC classification number: G06T5/003 , G06T5/50 , G06T7/269 , G06T2207/10016
Abstract: In embodiments of optical flow accounting for image haze, digital images may include objects that are at least partially obscured by a haze that is visible in the digital images, and an estimate of light that is contributed by the haze in the digital images can be determined. The haze can be cleared from the digital images based on the estimate of the light that is contributed by the haze, and clearer digital images can be generated. An optical flow between the clearer digital images can then be computed, and the clearer digital images refined based on the optical flow to further clear the haze from the images in an iterative process to improve visibility of the objects in the digital images.
Abstract translation: 在考虑图像雾度的光学流量的实施例中，数字图像可以包括由数字图像中可见的雾度至少部分地模糊的对象，并且可以确定由数字图像中的雾度贡献的光的估计 。 可以基于由雾度贡献的光的估计，从数字图像中清除雾度，并且可以产生更清晰的数字图像。 然后可以计算更清晰的数字图像之间的光流，并且基于光流改进更清晰的数字图像，以在迭代过程中进一步清除来自图像的雾度，以提高数字图像中的对象的可视性。
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公开(公告)号：US20150043806A1
公开(公告)日：2015-02-12
申请号：US13962604
申请日：2013-08-08
Applicant: Adobe Systems Incorporated
Inventor： Kevin Karsch , Kalyan Sunkavalli , Sunil Hadap , Nathan Carr , Hailin Jin
IPC: G06T7/00
CPC classification number: G06T15/506 , G06T7/536 , G06T11/60 , G06T15/50 , G06T19/20 , G06T2207/10024 , G06T2207/10028 , G06T2219/2021
Abstract: Image editing techniques are disclosed that support a number of physically-based image editing tasks, including object insertion and relighting. The techniques can be implemented, for example in an image editing application that is executable on a computing system. In one such embodiment, the editing application is configured to compute a scene from a single image, by automatically estimating dense depth and diffuse reflectance, which respectively form the geometry and surface materials of the scene. Sources of illumination are then inferred, conditioned on the estimated scene geometry and surface materials and without any user input, to form a complete 3D physical scene model corresponding to the image. The scene model may include estimates of the geometry, illumination, and material properties represented in the scene, and various camera parameters. Using this scene model, objects can be readily inserted and composited into the input image with realistic lighting, shadowing, and perspective.
Abstract translation: 公开了支持许多基于物理的图像编辑任务的图像编辑技术，包括对象插入和重新点亮。 这些技术可以被实现，例如在可在计算系统上执行的图像编辑应用中。 在一个这样的实施例中，编辑应用被配置为通过自动估计分别形成场景的几何和表面材料的密集深度和漫反射度来从单个图像计算场景。 然后推断照明源，根据估计的场景几何和表面材料进行调节，而无需任何用户输入，以形成对应于图像的完整3D物理场景模型。 场景模型可以包括在场景中表示的几何，照明和材料属性以及各种相机参数的估计。 使用这个场景模型，可以使用逼真的照明，阴影和透视，将对象轻松插入并合成到输入图像中。
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公开(公告)号：US20150030238A1
公开(公告)日：2015-01-29
申请号：US13953394
申请日：2013-07-29
Applicant: Adobe Systems Incorporated
Inventor： Jianchao Yang , Guang Chen , Jonathan Brandt , Hailin Jin , Elya Shechtman , Aseem Omprakash Agarwala
IPC: G06K9/62
CPC classification number: G06K9/627 , G06K9/4642
Abstract: A system may be configured as an image recognition machine that utilizes an image feature representation called local feature embedding (LFE). LFE enables generation of a feature vector that captures salient visual properties of an image to address both the fine-grained aspects and the coarse-grained aspects of recognizing a visual pattern depicted in the image. Configured to utilize image feature vectors with LFE, the system may implement a nearest class mean (NCM) classifier, as well as a scalable recognition algorithm with metric learning and max margin template selection. Accordingly, the system may be updated to accommodate new classes with very little added computational cost. This may have the effect of enabling the system to readily handle open-ended image classification problems.
Abstract translation: 系统可以被配置为利用称为局部特征嵌入（LFE）的图像特征表示的图像识别机器。 LFE能够生成捕获图像的显着视觉特性的特征向量，以解决识别图像中描绘的视觉图案的细粒度方面和粗粒度方面。 配置为利用具有LFE的图像特征向量，系统可以实现最近的等级均值（NCM）分类器，以及具有度量学习和最大边距模板选择的可缩放识别算法。 因此，可以更新系统以容纳新类别，而且增加了很少的计算成本。 这可能具有使系统能够容易地处理开放式图像分类问题的效果。
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公开(公告)号：US08934677B2
公开(公告)日：2015-01-13
申请号：US13724871
申请日：2012-12-21
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin
CPC classification number: G06T7/2033 , G06K9/3233 , G06K9/3241 , G06K9/3275 , G06K9/4652 , G06T5/001 , G06T7/246 , G06T7/579 , G06T7/70 , G06T2200/04 , G06T2207/10012 , G06T2207/10016 , G06T2207/20164 , G06T2207/30241 , G06T2207/30244 , H04N5/232 , H04N13/00 , H04N13/10 , H04N17/002
Abstract: An initialization technique that may, for example, be used in an adaptive reconstruction algorithm implemented by structure from motion (SFM) techniques. The initialization technique computes an initial reconstruction from a subset of frames in an image sequence. The initialization technique may be performed to determine and reconstruct a set of initial keyframes covering a portion of the image sequence according to the point trajectories. In the initialization technique, a set of temporally spaced keyframe candidates is determined and two initial keyframes are selected from the set of keyframe candidates. The two initial keyframes are reconstructed, and then one or more additional keyframes between the two initial keyframes are selected and reconstructed.
Abstract translation: 例如，可以用于通过运动（SFM）技术的结构实现的自适应重建算法中的初始化技术。 初始化技术从图像序列中的帧子集计算初始重建。 可以执行初始化技术以根据点轨迹来确定和重建覆盖图像序列的一部分的一组初始关键帧。 在初始化技术中，确定一组时间间隔的关键帧候选，并从该组关键帧候选中选择两个初始关键帧。 重建两个初始关键帧，然后选择和重建两个初始关键帧之间的一个或多个附加关键帧。
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公开(公告)号：US08923638B2
公开(公告)日：2014-12-30
申请号：US13725006
申请日：2012-12-21
Applicant: Adobe Systems Incorporated
Inventor： Hailin Jin
CPC classification number: G06T7/2033 , G06K9/3233 , G06K9/3241 , G06K9/3275 , G06K9/4652 , G06T5/001 , G06T7/246 , G06T7/579 , G06T7/70 , G06T2200/04 , G06T2207/10012 , G06T2207/10016 , G06T2207/20164 , G06T2207/30241 , G06T2207/30244 , H04N5/232 , H04N13/00 , H04N13/10 , H04N17/002
Abstract: A technique for selecting a particular reconstruction technique to be applied to an image sequence. The technique may analyze an input image sequence and, based on one or more characteristics of the image sequence, select a reconstruction technique as the appropriate technique for the image sequence from among a set of reconstruction techniques. For example, the set may include two or more of a rotation-based reconstruction technique, a plane-based reconstruction technique, and a general 3D reconstruction technique. The selection technique may be combined with the reconstruction techniques to produce a system that takes as input an image sequence or a set of point trajectories, selects an appropriate reconstruction technique, and applies the selected reconstruction technique to generate an estimate of camera motion and camera intrinsic parameters for the image sequence. The technique may be adapted to select among other types of techniques that may be applied to image sequences.
Abstract translation: 一种用于选择要应用于图像序列的特定重建技术的技术。 该技术可以分析输入图像序列，并且基于图像序列的一个或多个特征，从一组重建技术中选择重建技术作为图像序列的适当技术。 例如，该集合可以包括基于旋转的重建技术，基于平面的重建技术和一般的3D重建技术中的两个或更多个。 选择技术可以与重建技术组合以产生将图像序列或一组点轨迹作为输入的系统，选择适当的重建技术，并且应用所选择的重建技术来生成相机运动和相机内在的估计 图像序列的参数。 该技术可以适于选择可应用于图像序列的其它类型的技术。
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