公开(公告)号：US09922314B2

公开(公告)日：2018-03-20

申请号：US14409072

申请日：2012-10-26

Applicant: Zhe Lin

Inventor： Guihong Chen ,  Chuirui Qiu ,  Bifeng Huang

IPC: G06Q20/20 ,  G07G1/00 ,  G07G1/12 ,  B41J29/02 ,  B41J29/13 ,  B41J3/46 ,  H04N1/00

CPC classification number: G06Q20/20 ,  B41J3/46 ,  B41J29/02 ,  B41J29/13 ,  G07G1/0018 ,  G07G1/12 ,  H04N1/00204 ,  H04N1/00326 ,  H04N1/00392 ,  H04N1/00493 ,  H04N1/00543 ,  H04N1/00557

Abstract: An embedded touch POS machine which integrates input and output, remote signal transmission and reception, and printing, is provided. The embedded touch POS machine comprises a touch screen display, a printer and a mounting bracket. The mounting bracket comprises a box-shaped bracket body constructed of a transverse plate and a vertical plate and a movable bracket lid mounted on a top of the box-shaped bracket body. The touch screen display is disposed on a top face of the bracket lid, the printing head is disposed to a side of a bottom face of the bracket lid, the printer body and the printing paper scroll are disposed on the transverse plate of the bracket body, and, the printing board is located at a bottom face of the transverse plate of the bracket body.

公开(公告)号：US08917948B2

公开(公告)日：2014-12-23

申请号：US13481491

申请日：2012-05-25

Applicant: Hailin Jin ,  Alper Ayvaci ,  Zhe Lin ,  Scott D. Cohen

Inventor： Hailin Jin ,  Alper Ayvaci ,  Zhe Lin ,  Scott D. Cohen

IPC: G06K9/40 ,  G06T3/40

CPC classification number: G06T3/4053 ,  G06T3/4076 ,  G06T5/002

Abstract: A method, system, and computer-readable storage medium are disclosed for denoising an image sequence. A first patch is determined in a first frame in an image sequence comprising a plurality of frames. The first patch comprises a subset of image data in the first frame. Locations of a plurality of corresponding patches are determined in a neighboring set of the plurality of frames. One or more neighboring related patches are determined for each of the plurality of corresponding patches in a same frame as the respective one of the corresponding patches. A denoised first patch is generated by averaging image data in the one or more neighboring related patches in the neighboring set of the plurality of frames.

Abstract translation: 公开了一种用于对图像序列进行去噪的方法，系统和计算机可读存储介质。 在包括多个帧的图像序列中的第一帧中确定第一贴片。 第一贴片包括第一帧中的图像数据的子集。 在多个帧的相邻集合中确定多个对应的片段的位置。 在与相应的补丁相应的一个相同的帧中，为多个对应的补丁中的每一个确定一个或多个相邻的相关补丁。 通过对多个帧的相邻集合中的一个或多个相邻相关片段中的图像数据进行平均来生成去噪的第一贴片。

公开(公告)号：US08805116B2

公开(公告)日：2014-08-12

申请号：US13434061

申请日：2012-03-29

Applicant: Zhe Lin ,  Jonathan W. Brandt

Inventor： Zhe Lin ,  Jonathan W. Brandt

IPC: G06F9/00 ,  G06F17/30 ,  G06K9/46

CPC classification number: G06F17/30262 ,  G06F17/3025 ,  G06K9/4676

Abstract: For each image of a set of images, the each image is characterized with a set of fixed-orientation texture descriptors and a set of color descriptors. The set of images is indexed in a color index and a texture index. Similarly, a query image is characterized with a set of fixed-orientation texture descriptors. The set of fixed orientation texture descriptors of the query image includes a set of fixed orientation descriptors for each of a set of rotated query images, and a set of color descriptors of the query image. A rotated local Bag-of-Features (BoF) operation is performed upon the set of rotated query images and the set of images. Each of the set of images is ranked based on the rotated local Bag-of-Features operation.

Abstract translation: 对于一组图像的每个图像，每个图像用一组固定方向纹理描述符和一组颜色描述符来表征。 该图像集合以颜色索引和纹理索引为索引。 类似地，查询图像用一组固定方向纹理描述符来表征。 查询图像的固定方向纹理描述符的集合包括用于一组旋转查询图像中的每一个的一组固定方位描述符和查询图像的一组颜色描述符。 在旋转的查询图像和图像集合上执行旋转的局部特征（BoF）操作。 基于旋转的本地Bag-of-Features操作对该组图像中的每一个进行排名。

公开(公告)号：US20140089326A1

公开(公告)日：2014-03-27

申请号：US13624615

申请日：2012-09-21

Applicant: Zhe Lin ,  Jonathan W. Brandt

Inventor： Zhe Lin ,  Jonathan W. Brandt

IPC: G06F17/30

CPC classification number: G06F17/30259

Abstract: Query object localization, segmentation, and retrieval are disclosed. A query image may be received that includes a query object. Based on respective spatially constrained similarity measures between the query image and a plurality of images from an image database, at least some of the plurality of images may be identified and/or retrieved and a location of the query object in the query image may be estimated. The query object may then be automatically segmented from the query image based on the estimated query object location. In some embodiments, the retrieval, localization and/or segmentation may be iterated.

Abstract translation: 公开了查询对象的定位，分割和检索。 可以接收包括查询对象的查询图像。 基于来自图像数据库的查询图像和多个图像之间的相应的空间约束相似性度量，可以识别和/或检索多个图像中的至少一些图像，并且可以估计查询图像中查询对象的位置 。 然后可以基于估计的查询对象位置从查询图像中自动地分割查询对象。 在一些实施例中，可重复检索，定位和/或分割。

公开(公告)号：US20130121600A1

公开(公告)日：2013-05-16

申请号：US13434028

申请日：2012-03-29

Applicant: Zhe Lin ,  Jonathan W. Brandt

Inventor： Zhe Lin ,  Jonathan W. Brandt

IPC: G06K9/62

CPC classification number: G06F17/30262 ,  G06F17/3025 ,  G06K9/4676

Abstract: Each image of a set of images is characterized with a set of sparse feature descriptors and a set of dense feature descriptors. In some embodiments, both the set of sparse feature descriptors and the set of dense feature descriptors are calculated based on a fixed rotation for computing texture descriptors, while color descriptors are rotation invariant. In some embodiments, the descriptors of both sparse and dense features are then quantized into visual words. Each database image is represented by a feature index including the visual words computed from both sparse and dense features. A query image is characterized with the visual words computed from both sparse and dense features of the query image. A rotated local Bag-of-Features (BoF) operation is performed upon a set of rotated query images against the set of database images. Each of the set of images is ranked based on the rotated local Bag-of-Features operation.

Abstract translation: 一组图像的每个图像用一组稀疏特征描述符和一组密集特征描述符来表征。 在一些实施例中，基于用于计算纹理描述符的固定旋转来计算稀疏特征描述符集合和密集特征描述符集合，而颜色描述符是旋转不变量。 在一些实施例中，稀疏和密集特征的描述符然后被量化为视觉词。 每个数据库图像由特征索引表示，包括从稀疏和密集特征计算的视觉词。 查询图像的特征在于从查询图像的稀疏和密集特征计算的视觉词。 一组旋转的本地特征（BoF）操作是针对一组数据库图像进行旋转的查询图像执行的。 基于旋转的本地Bag-of-Features操作对该组图像中的每一个进行排名。

公开(公告)号：US20130060766A1

公开(公告)日：2013-03-07

申请号：US13552596

申请日：2012-07-18

Applicant: Zhe Lin ,  Jonathan W. Brandt ,  Xiaohui Shen

Inventor： Zhe Lin ,  Jonathan W. Brandt ,  Xiaohui Shen

IPC: G06F17/30

CPC classification number: G06F17/30259 ,  G06F17/3025 ,  G06F17/30256 ,  G06F17/30262 ,  G06F17/30265 ,  G06F17/3028 ,  G06K9/4676 ,  G06K9/6211 ,  G06K9/6212 ,  G06Q30/02

Abstract: Methods, apparatus, and computer-readable storage media for k-NN re-ranking. Based on retrieved images and localized objects, a k-NN re-ranking method may use the k-nearest neighbors of a query to refine query results. Given the top k retrieved images and their localized objects, each k-NN object may be used as a query to perform a search. A database image may have different ranks when using those k-nearest neighbors as queries. Accordingly, a new score for each database image may be collaboratively determined by those ranks, and re-ranking may be performed using the new scores to improve the search results. The k-NN re-ranking technique may be performed two or more times, each time on a new set of k-nearest neighbors, to further refine the search results.

Abstract translation: 用于k-NN重新排序的方法，装置和计算机可读存储介质。 基于检索到的图像和本地化对象，k-NN重排序方法可以使用查询的k个最近邻居来优化查询结果。 给定顶部k个检索到的图像及其本地化对象，每个k-NN对象可以用作查询来执行搜索。 当使用这些k个最近邻居作为查询时，数据库图像可能具有不同的等级。 因此，每个数据库图像的新分数可以由这些等级协同确定，并且可以使用新分数来执行重新排序以改善搜索结果。 k-NN重新排序技术可以每次在一组新的k个最近邻居上执行两次或更多次，以进一步优化搜索结果。

公开(公告)号：US20130034299A1

公开(公告)日：2013-02-07

申请号：US13565411

申请日：2012-08-02

Applicant: Zhe Lin ,  Scott D. Cohen ,  Jen-Chan Chien ,  Sarah A. Kong ,  Jianchao Yang

Inventor： Zhe Lin ,  Scott D. Cohen ,  Jen-Chan Chien ,  Sarah A. Kong ,  Jianchao Yang

IPC: G06K9/32

CPC classification number: G06T3/4053

Abstract: Methods and systems for image upscaling are disclosed. In one embodiment, a low frequency band image intermediate is obtained from an input image. The input image is upsampled by a scale factor to obtain an upsampled image intermediate. A result image is estimated based at least in part on the upsampled image intermediate, the low frequency band image intermediate, and the input image, wherein the input image is of a smaller scale than the result image.

Abstract translation: 公开了用于图像放大的方法和系统。 在一个实施例中，从输入图像获得低频带图像中间体。 输入图像由比例因子上采样，以获得上采样图像中间值。 至少部分地基于上采样图像中间，低频带图像中间和输入图像来估计结果图像，其中输入图像比结果图像小一些。

公开(公告)号：US09146941B2

公开(公告)日：2015-09-29

申请号：US13566677

申请日：2012-08-03

Applicant: Zhe Lin ,  Jonathan Brandt

Inventor： Zhe Lin ,  Jonathan Brandt

IPC: G06K9/62 ,  G06F17/30

CPC classification number: G06F17/30268 ,  G06F17/30247

Abstract: An approach is described for automatically tagging a single image or multiple images. The approach, in one example embodiment, is based on a graph-based framework that exploits both visual similarity between images and tag correlation within individual images. The problem is formulated in the context of semi-supervised learning, where a graph modeled as a Gaussian Markov Random Field (MRF) is solved by minimizing an objective function (the image tag score function) using an iterative approach. The iterative approach, in one embodiment, comprises: (1) fixing tags and propagating image tag likelihood values from labeled images to unlabeled images, and (2) fixing images and propagating image tag likelihood based on tag correlation.

Abstract translation: 描述了一种自动标记单个图像或多个图像的方法。 在一个示例性实施例中，该方法基于图形框架，其利用图像之间的视觉相似性和各个图像内的标签相关性。 该问题在半监督学习的背景下形成，其中通过使用迭代方法最小化目标函数（图像标签评分函数）来解决建模为高斯马尔可夫随机场（MRF）的图形。 在一个实施例中，迭代方法包括：（1）固定标签并将图像标签似然值从标记的图像传播到未标记的图像，以及（2）基于标签相关性固定图像和传播图像标签似然性。

公开(公告)号：US20150248654A1

公开(公告)日：2015-09-03

申请号：US14409072

申请日：2012-10-25

Applicant: Zhe LIN

Inventor： Guihong Chen ,  Chuirui Qiu ,  Bifeng Huang

IPC: G06Q20/20 ,  H04N1/00

CPC classification number: G06Q20/20 ,  B41J3/46 ,  B41J29/02 ,  B41J29/13 ,  G07G1/0018 ,  G07G1/12 ,  H04N1/00204 ,  H04N1/00326 ,  H04N1/00392 ,  H04N1/00493 ,  H04N1/00543 ,  H04N1/00557

Abstract: An embedded touch POS machine which integrates input and output, remote signal transmission and reception, and printing, is provided. The embedded touch POS machine comprises a touch screen display, a printer and a mounting bracket. The mounting bracket comprises a box-shaped bracket body constructed of a transverse plate and a vertical plate and a movable bracket lid mounted on a top of the box-shaped bracket body. The touch screen display is disposed on a top face of the bracket lid, the printing head is disposed to a side of a bottom face of the bracket lid, the printer body and the printing paper scroll are disposed on the transverse plate of the bracket body, and, the printing board is located at a bottom face of the transverse plate of the bracket body.

Abstract translation: 提供集输入和输出，远程信号发送和接收以及打印的嵌入式触摸POS机。 嵌入式触摸POS机包括触摸屏显示器，打印机和安装支架。 安装支架包括一个由横板和垂直板构成的箱形支架体，以及安装在盒形支架主体顶部的活动支架盖。 触摸屏显示器设置在支架盖的顶面上，打印头设置在托架盖底面的一侧，打印机主体和打印纸卷轴设置在支架主体的横板上 ，并且印刷基板位于支架主体的横板的底面。

公开(公告)号：US20140037195A1

公开(公告)日：2014-02-06

申请号：US13566677

申请日：2012-08-03

Applicant: Zhe Lin ,  Jonathan Brandt

Inventor： Zhe Lin ,  Jonathan Brandt

IPC: G06K9/68

CPC classification number: G06F17/30268 ,  G06F17/30247

Abstract: An approach is described for automatically tagging a single image or multiple images. The approach, in one example embodiment, is based on a graph-based framework that exploits both visual similarity between images and tag correlation within individual images. The problem is formulated in the context of semi-supervised learning, where a graph modeled as a Gaussian Markov Random Field (MRF) is solved by minimizing an objective function (the image tag score function) using an iterative approach. The iterative approach, in one embodiment, comprises: (1) fixing tags and propagating image tag likelihood values from labeled images to unlabeled images, and (2) fixing images and propagating image tag likelihood based on tag correlation.

Abstract translation: 描述了一种自动标记单个图像或多个图像的方法。 在一个示例性实施例中，该方法基于图形框架，其利用图像之间的视觉相似性和各个图像内的标签相关性。 该问题在半监督学习的背景下形成，其中通过使用迭代方法最小化目标函数（图像标签评分函数）来解决建模为高斯马尔可夫随机场（MRF）的图形。 在一个实施例中，迭代方法包括：（1）固定标签并将图像标签似然值从标记的图像传播到未标记的图像，以及（2）基于标签相关性固定图像和传播图像标签似然性。