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公开(公告)号：US20160307143A1
公开(公告)日：2016-10-20
申请号：US14689320
申请日：2015-04-17
Applicant: Xerox Corporation
Inventor： Michael C. Mongeon , Robert Loce , Matthew Shreve
CPC classification number: G06Q10/063114 , G06K9/00335 , G06K9/00771 , H04N5/77
Abstract: When monitoring a workspace to determine whether scheduled tasks or chores are completed according to a predetermined schedule, a video monitoring system monitors a region of interest (ROI) to identify employee-generated signals representing completion of a scheduled task. An employee makes a mark or gesture in the ROI monitored by the video monitoring system and the system analyzes pixels in each captured frame of the ROI to identify an employee signal, map the signal to a corresponding scheduled task, update the task as having been completed upon receipt of the employee signal, and alert a manager of the facility as to whether the task has been completed or not.
Abstract translation: 当监视工作空间以根据预定的时间表完成调度任务或排班时，视频监控系统监视感兴趣区域（ROI）以识别表示已完成预约任务的员工生成的信号。 员工在由视频监控系统监控的ROI中进行标记或手势，并且系统分析ROI的每个拍摄帧中的像素，以识别员工信号，将信号映射到相应的计划任务，将任务更新为已完成 在接收到雇员信号之后，并通知设施的管理者该任务是否已经完成。
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2.发明申请公开(公告)号：US20150278616A1
公开(公告)日：2015-10-01
申请号：US14227035
申请日：2014-03-27
Applicant: Xerox Corporation
Inventor： Qun Li , Edgar A. Bernal , Matthew Shreve , Robert P. Loce
CPC classification number: G06K9/00825 , G06K9/00744 , G06K9/6269 , G06T7/194 , G06T7/215 , G06T7/251 , G06T7/254 , G06T2207/10048 , G06T2207/20032 , G06T2207/20076 , G06T2207/20081 , G06T2207/30232 , G06T2207/30242
Abstract: A method for removing false foreground image content in a foreground detection process performed on a video sequence includes, for each current frame, comparing a feature value of each current pixel against a feature value of a corresponding pixel in a background model. The each current pixel is classified as belonging to one of a candidate foreground image and a background based on the comparing. A first classification image representing the candidate foreground image is generated using the current pixels classified as belonging to the candidate foreground image. The each pixel in the first classification image is classified as belonging to one of a foreground image and a false foreground image using a previously trained classifier. A modified classification image is generated for representing the foreground image using the pixels classified as belonging to the foreground image while the pixels classified as belonging to the false foreground image are removed.
Abstract translation: 在对视频序列执行的前景检测处理中去除假前景图像内容的方法包括：对于每个当前帧，将每个当前像素的特征值与背景模型中相应像素的特征值进行比较。 基于比较，将每个当前像素分类为属于候选前景图像和背景中的一个。 使用分类为属于候选前景图像的当前像素来生成表示候选前景图像的第一分类图像。 使用先前训练的分类器将第一分类图像中的每个像素分类为属于前景图像和假前景图像之一。 生成用于使用分类为属于前景图像的像素来表示前景图像的修改后的分类图像，而分类为属于假前景图像的像素被去除。
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公开(公告)号：US20240339560A1
公开(公告)日：2024-10-10
申请号：US18745409
申请日：2024-06-17
Applicant: Xerox Corporation
Inventor： Evgeniy Bart , Yunda Wang , Matthew Shreve
IPC: H01L33/00 , H01L21/683 , H01L25/075 , H01L33/62
CPC classification number: H01L33/0095 , H01L21/6835 , H01L25/0753 , H01L33/62 , H01L2221/68354 , H01L2221/68368 , H01L2933/0066
Abstract: Data representations are formed of a target substrate and a plurality of donor coupons that are incompletely filled with functional chips. The data representations are abstracted into a current state description of the target substrate and the donor coupons and input into a machine learning model that has been trained on previous mass transfer sequences. An optimal output of the machine learning model defines at least a selected one or more of the donor coupons and corresponding functional chips of the selected one or more of the donor coupons used to fill the vacancies. A parallel transfer of the corresponding functional chips is performed to fill the vacancies on the target substrate using the selected one or more of the donor coupons.
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公开(公告)号：US20170262723A1
公开(公告)日：2017-09-14
申请号：US15064167
申请日：2016-03-08
Applicant: Xerox Corporation
Inventor： Vladimir Kozitsky , Matthew Shreve , Orhan Bulan
CPC classification number: G06K9/325 , G06K9/3216 , G06K9/4628 , G06K9/6267 , G06K9/6857 , G06K2209/15
Abstract: Methods, systems, and processor-readable media for the detection and classification of license plates. In an example embodiment, an image of a vehicle can be captured with an image-capturing unit. A license plate region can then be located in the captured image of the vehicle by extracting a set of candidate regions from the image utilizing a weak classifier. A set of candidate regions can be ranked utilizing a secondary strong classifier. The captured image can then be classified according to a confidence driven classification based on classification criteria determined by the weak classifier and the secondary strong classifier.
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公开(公告)号：US20160148076A1
公开(公告)日：2016-05-26
申请号：US14561512
申请日：2014-12-05
Applicant: Xerox Corporation
Inventor： Vladimir Kozitsky , Matthew Shreve , Aaron M. Burry
CPC classification number: G06K9/627 , G06K9/00771 , G06K9/325 , G06K2209/15 , G06N99/005 , G08G1/0175
Abstract: Systems and methods for automating an image rejection process. Features including texture, spatial structure, and image quality characteristics can be extracted from one or more images to train a classifier. Features can be calculated with respect to a test image for submission of the features to the classifier, given an operating point corresponding to a desired false positive rate. One or more inputs can be generated from the classifier as a confidence value corresponding to a likelihood of, for example: a license plate being absent in the image, the license plate being unreadable, or the license plate being obstructed. The confidence value can be compared against a threshold to determine if the image(s) should be removed from a human review pipeline, thereby reducing images requiring human review.
Abstract translation: 用于自动化镜像抑制过程的系统和方法。 可以从一个或多个图像中提取包括纹理，空间结构和图像质量特征的特征来训练分类器。 给定对应于所需假阳性率的操作点，可以相对于用于将特征提交给分类器的测试图像来计算特征。 可以从分类器产生一个或多个输入作为对应于例如图像中不存在牌照，牌照不可读或牌照妨碍的可能性的置信度值。 可以将置信度值与阈值进行比较，以确定图像是否应从人类审查管道中移除，从而减少需要人工审查的图像。
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Patent Agency Ranking
6.发明授权公开(公告)号：US09275289B2
公开(公告)日：2016-03-01
申请号：US14227035
申请日：2014-03-27
Applicant: Xerox Corporation
Inventor： Qun Li , Edgar A. Bernal , Matthew Shreve , Robert P. Loce
CPC classification number: G06K9/00825 , G06K9/00744 , G06K9/6269 , G06T7/194 , G06T7/215 , G06T7/251 , G06T7/254 , G06T2207/10048 , G06T2207/20032 , G06T2207/20076 , G06T2207/20081 , G06T2207/30232 , G06T2207/30242
Abstract: A method for removing false foreground image content in a foreground detection process performed on a video sequence includes, for each current frame, comparing a feature value of each current pixel against a feature value of a corresponding pixel in a background model. The each current pixel is classified as belonging to one of a candidate foreground image and a background based on the comparing. A first classification image representing the candidate foreground image is generated using the current pixels classified as belonging to the candidate foreground image. The each pixel in the first classification image is classified as belonging to one of a foreground image and a false foreground image using a previously trained classifier. A modified classification image is generated for representing the foreground image using the pixels classified as belonging to the foreground image while the pixels classified as belonging to the false foreground image are removed.
Abstract translation: 在对视频序列执行的前景检测处理中去除假前景图像内容的方法包括：对于每个当前帧，将每个当前像素的特征值与背景模型中相应像素的特征值进行比较。 基于比较，将每个当前像素分类为属于候选前景图像和背景中的一个。 使用分类为属于候选前景图像的当前像素来生成表示候选前景图像的第一分类图像。 使用先前训练的分类器将第一分类图像中的每个像素分类为属于前景图像和假前景图像之一。 生成用于使用分类为属于前景图像的像素来表示前景图像的修改后的分类图像，而分类为属于假前景图像的像素被去除。
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公开(公告)号：US20220410273A1
公开(公告)日：2022-12-29
申请号：US17356627
申请日：2021-06-24
Applicant: PALO ALTO RESEARCH CENTER INCORPORATED , XEROX CORPORATION
Inventor： Robert R. Price , Raja Bala , Svyatoslav Korneev , Christoforos Somarakis , Matthew Shreve , Adrian Lew , Palghat Ramesh
IPC: B22F10/80 , G06T17/00 , G06K9/00 , G06K9/62 , G06T7/64 , G06K15/02 , G06T7/00 , G05B13/04 , G05B13/02 , B22D23/00 , B22F10/22 , B22F12/90 , B33Y30/00 , B33Y50/00
Abstract: A three-dimensional (3D) printer includes a nozzle and a camera configured to capture a real image or a real video of a liquid metal while the liquid metal is positioned at least partially within the nozzle. The 3D printer also includes a computing system configured to perform operations. The operations include generating a model of the liquid metal positioned at least partially within the nozzle. The operations also include generating a simulated image or a simulated video of the liquid metal positioned at least partially within the nozzle based at least partially upon the model. The operations also include generating a labeled dataset that comprises the simulated image or the simulated video and a first set of parameters. The operations also include reconstructing the liquid metal in the real image or the real video based at least partially upon the labeled dataset.
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公开(公告)号：US09911055B2
公开(公告)日：2018-03-06
申请号：US15064167
申请日：2016-03-08
Applicant: Xerox Corporation
Inventor： Vladimir Kozitsky , Matthew Shreve , Orhan Bulan
CPC classification number: G06K9/325 , G06K9/3216 , G06K9/4628 , G06K9/6267 , G06K9/6857 , G06K2209/15
Abstract: Methods, systems, and processor-readable media for the detection and classification of license plates. In an example embodiment, an image of a vehicle can be captured with an image-capturing unit. A license plate region can then be located in the captured image of the vehicle by extracting a set of candidate regions from the image utilizing a weak classifier. A set of candidate regions can be ranked utilizing a secondary strong classifier. The captured image can then be classified according to a confidence driven classification based on classification criteria determined by the weak classifier and the secondary strong classifier.
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公开(公告)号：US20240420409A1
公开(公告)日：2024-12-19
申请号：US18822393
申请日：2024-09-02
Applicant: XEROX CORPORATION
Inventor： Gregory M. Youngblood , Matthew Shreve , Mark J. Stefik , Robert Thomas Krivacic , Lester D. Nelson , Jacob Le
Abstract: A system and method for translating a 3D visualization to a 2D visualization is provided. Data for a 3D visualization is received and includes layers of voxels that are processed to determine a type of terrain and color associated with the terrain type. Each voxel in a base layer of the 3D visualization is transformed into a tile of pixels for a 2D visualization. The color associated with the layers is assigned to the tiles by identifying, for each such layer, a marker for each voxel in that layer that indicates a presence or absence of the terrain type for that layer and applying the color associated with the layer to at least a portion of the tiles based on the markers. When multiple colors are applied to one of the tiles, the color associated with the layer furthest from the base layer is selected. The 2D visualization is output.
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公开(公告)号：US11983171B2
公开(公告)日：2024-05-14
申请号：US18219333
申请日：2023-07-07
Applicant: Xerox Corporation
Inventor： Matthew Shreve , Francisco E. Torres , Raja Bala , Robert R. Price , Pei Li
CPC classification number: G06F16/2379 , G06N20/00
Abstract: A method of labeling a dataset includes inputting a testing set comprising a plurality of input data samples into a plurality of pre-trained machine learning models to generate a set of embeddings output by the plurality of pre-trained machine learning models. The method further includes performing an iterative cluster labeling algorithm that includes generating a plurality of clusterings from the set of embeddings, analyzing the plurality of clusterings to identify a target embedding with a highest duster quality, analyzing the target embedding to determine a compactness for each of the plurality of clusterings of the target embedding, and identifying a target cluster among the plurality of clusterings of the target embedding based on the compactness. The method further includes assigning pseudo-labels to the subset of the plurality of input data samples that are members of the target duster.
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