公开(公告)号：US20190139319A1

公开(公告)日：2019-05-09

申请号：US15804908

申请日：2017-11-06

Applicant: ADOBE SYSTEMS INCORPORATED

Inventor： Jonathan Eisenmann ,  Geoffrey Alan Oxholm ,  Elya Shechtman ,  Bryan Russell

IPC: G06T19/20 ,  G06T15/20

CPC classification number: G06T19/20 ,  G06T15/20 ,  G06T2219/2004 ,  G06T2219/2016

Abstract: Embodiments disclosed herein provide systems, methods, and computer storage media for automatically aligning a 3D camera with a 2D background image. An automated image analysis can be performed on the 2D background image, and a classifier can predict whether the automated image analysis is accurate within a selected confidence level. As such, a feature can be enabled that allows a user to automatically align the 3D camera with the 2D background image. For example, where the automated analysis detects a horizon and one or more vanishing points from the background image, the 3D camera can be automatically transformed to align with the detected horizon and to point at a detected horizon-located vanishing point. In some embodiments, 3D objects in a 3D scene can be pivoted and the 3D camera dollied forward or backwards to reduce changes to the framing of the 3D composition resulting from the 3D camera transformation.

公开(公告)号：US10089764B2

公开(公告)日：2018-10-02

申请号：US14185507

申请日：2014-02-20

Applicant: Adobe Systems Incorporated

Inventor： Elya Shechtman ,  Daniel R. Goldman ,  Aliakbar Darabi ,  Nima Khademi Kalantari

IPC: G06T11/60 ,  G06T5/00

Abstract: Variable patch shape synthesis techniques are described. In one or more implementations, a plurality of patches are computed from one or more images, at least one of the plurality of patches having a different shape than another one of the plurality of patches. The shapes define an area to be considered for use in a patch synthesis technique. The patch synthesis technique is performed to edit an image using the computed plurality of patches having the different shapes.

公开(公告)号：US20180122044A1

公开(公告)日：2018-05-03

申请号：US15377875

申请日：2016-12-13

Applicant: Adobe Systems Incorporated

Inventor： Xue Bai ,  Elya Shechtman ,  Sylvain Philippe Paris

IPC: G06T3/20 ,  G06T3/40 ,  G06T7/60

CPC classification number: G06T3/20 ,  G06T3/40 ,  G06T5/005 ,  G06T7/60

Abstract: Environmental map generation techniques and systems are described. A digital image is scaled to achieve a target aspect ratio using a content aware scaling technique. A canvas is generated that is dimensionally larger than the scaled digital image and the scaled digital image is inserted within the canvas thereby resulting in an unfilled portion of the canvas. An initially filled canvas is then generated by filling the unfilled portion using a content aware fill technique based on the inserted digital image. A plurality of polar coordinate canvases is formed by transforming original coordinates of the canvas into polar coordinates. The unfilled portions of the polar coordinate canvases are filled using a content-aware fill technique that is initialized based on the initially filled canvas. An environmental map of the digital image is generated by combining a plurality of original coordinate canvas portions formed from the polar coordinate canvases.

公开(公告)号：US20180096454A1

公开(公告)日：2018-04-05

申请号：US15286245

申请日：2016-10-05

Applicant: ADOBE SYSTEMS INCORPORATED

Inventor： Sohrab Amirghodsi ,  Aliakbar Darabi ,  Elya Shechtman

IPC: G06T3/40 ,  G06T7/00

CPC classification number: G06T3/40 ,  G06T3/4053 ,  G06T7/0081 ,  G06T7/11 ,  G06T2207/10004

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed at image synthesis utilizing sampling of patch correspondence information between iterations at different scales. A patch synthesis technique can be performed to synthesize a target region at a first image scale based on portions of a source region that are identified by the patch synthesis technique. The image can then be sampled to generate an image at a second image scale. The sampling can include generating patch correspondence information for the image at the second image scale. Invalid patch assignments in the patch correspondence information at the second image scale can then be identified, and valid patches can be assigned to the pixels having invalid patch assignments. Other embodiments may be described and/or claimed.

公开(公告)号：US09881413B2

公开(公告)日：2018-01-30

申请号：US15178072

申请日：2016-06-09

Applicant: Adobe Systems Incorporated

Inventor： Jakub Fiser ,  Ondrej Jamri{hacek over (s)}ka ,  Michal Luká{hacek over (c)} ,  Elya Shechtman ,  Paul J. Asente ,  Jingwan Lu ,  Daniel Sýkora

IPC: G06T15/50 ,  G06T15/02 ,  G06T15/80 ,  G06T15/60

CPC classification number: G06T15/503 ,  G06T11/60 ,  G06T15/02 ,  G06T15/60 ,  G06T15/80 ,  G06T19/20 ,  G06T2219/2024

Abstract: Techniques for illumination-guided example-based stylization of 3D renderings are described. In implementations, a source image and a target image are obtained, where each image includes a multi-channel image having at least a style channel and multiple light path expression (LPE) channels having light propagation information. Then, the style channel of the target image is synthesized to mimic a stylization of individual illumination effects from the style channel of the source image. As part of the synthesizing, the light propagation information is applied as guidance for synthesis of the style channel of the target image. Based on the guidance, the stylization of individual illumination effects from the style channel of the source image is transferred to the style channel of the target image. Based on the transfer, the style channel of the target image is then generated for display of the target image via a display device.

公开(公告)号：US09881376B2

公开(公告)日：2018-01-30

申请号：US14444996

申请日：2014-07-28

Applicant: Adobe Systems Incorporated

Inventor： Elya Shechtman ,  Shai Bagon ,  Aseem O. Agarwala

IPC: G06F17/00 ,  G06T7/00 ,  G06T13/80 ,  G06K9/00 ,  G06T3/00 ,  G06T7/38

CPC classification number: G06T7/38 ,  G06K9/00718 ,  G06T3/0006 ,  G06T3/0056 ,  G06T13/80 ,  G06T2207/20036

Abstract: A method, system, and computer-readable storage medium for performing content based transitions between images. Image content within each image of a set of images are analyzed to determine at least one respective characteristic metric for each image. A respective transition score for each pair of at least a subset of the images is determined with respect to each transition effect of a plurality of transition effects based on the at least one respective characteristic metric for each image. Transition effects implementing transitions between successive images for a sequence of the images are determined based on the transition scores. An indication of the determined transition effects is stored. The determined transition effects are useable to present the images in a slideshow or other image sequence presentation.

公开(公告)号：US20170213112A1

公开(公告)日：2017-07-27

申请号：US15005855

申请日：2016-01-25

Applicant: Adobe Systems Incorporated

Inventor： Ian Sachs ,  Xiaoyong Shen ,  Sylvain Paris ,  Aaron Hertzmann ,  Elya Shechtman ,  Brian Price

IPC: G06K9/66 ,  G06K9/46 ,  G06T7/00

CPC classification number: G06K9/66 ,  G06K9/00228 ,  G06K9/4604 ,  G06T7/11 ,  G06T7/73 ,  G06T7/90 ,  G06T2207/20084 ,  G06T2207/30201

Abstract: Systems and methods are disclosed for segregating target individuals represented in a probe digital image from background pixels in the probe digital image. In particular, in one or more embodiments, the disclosed systems and methods train a neural network based on two or more of training position channels, training shape input channels, training color channels, or training object data. Moreover, in one or more embodiments, the disclosed systems and methods utilize the trained neural network to select a target individual in a probe digital image. Specifically, in one or more embodiments, the disclosed systems and methods generate position channels, training shape input channels, and color channels corresponding the probe digital image, and utilize the generated channels in conjunction with the trained neural network to select the target individual.

公开(公告)号：US09098885B2

公开(公告)日：2015-08-04

申请号：US13871597

申请日：2013-04-26

Applicant: Adobe Systems Incorporated

Inventor： Elya Shechtman ,  Jue Wang ,  Hyunjoon Lee ,  Seungyong Lee

IPC: H04N17/00 ,  H04N17/02 ,  G06T5/00 ,  G06T7/00 ,  G06T3/60 ,  G06T3/00

CPC classification number: H04N5/23229 ,  G06T3/00 ,  G06T3/608 ,  G06T5/00 ,  G06T5/006 ,  G06T7/80 ,  G06T15/20

Abstract: Techniques and apparatus for automatic upright adjustment of digital images. An automatic upright adjustment technique is described that may provide an automated approach for straightening up slanted features in an input image to improve its perceptual quality. This correction may be referred to as upright adjustment. A set of criteria based on human perception may be used in the upright adjustment. A reprojection technique that implements an optimization framework is described that yields an optimal homography for adjustment based on the criteria and adjusts the image according to new camera parameters generated by the optimization. An optimization-based camera calibration technique is described that simultaneously estimates vanishing lines and points as well as camera parameters for an image; the calibration technique may, for example, be used to generate estimates of camera parameters and vanishing points and lines that are input to the reprojection technique.

Abstract translation: 用于数字图像自动竖直调整的技术和设备。 描述了自动立式调节技术，其可以提供用于矫正输入图像中的倾斜特征的自动化方法，以提高其感知质量。 这种校正可以被称为直立调节。 可以在直立式调整中使用基于人类感知的一组标准。 描述了实现优化框架的重投影技术，其基于标准产生用于调整的最佳单应性，并且根据由优化生成的新的相机参数来调整图像。 描述了基于优化的相机校准技术，其同时估计图像的消失线和点以及相机参数; 例如，校准技术可以用于生成输入到重投影技术的相机参数和消失点和线的估计。

公开(公告)号：US20150145862A1

公开(公告)日：2015-05-28

申请号：US14092210

申请日：2013-11-27

Applicant: Adobe Systems Incorporated

Inventor： Siying Liu ,  Kalyan Sunkavalli ,  Nathan A. Carr ,  Elya Shechtman

IPC: G06T15/04 ,  G06T19/20 ,  G06T17/20

CPC classification number: G06T11/001 ,  G06K9/52 ,  G06K9/6211 ,  G06T7/49

Abstract: Texture modeling techniques for image data are described. In one or more implementations, texels in image data are discovered by one or more computing devices, each texel representing an element that repeats to form a texture pattern in the image data. Regularity of the texels in the image data is modeled by the one or more computing devices to define translations and at least one other transformation of texels in relation to each other.

Abstract translation: 描述图像数据的纹理建模技术。 在一个或多个实现中，图像数据中的纹理元素由一个或多个计算设备发现，每个纹素表示在图像数据中重复形成纹理图案的元素。 图像数据中的纹理的规则性由一个或多个计算设备建模，以定义相对于彼此的翻译和纹素的至少一个其他变换。

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。