公开(公告)号：US08774462B2

公开(公告)日：2014-07-08

申请号：US13768883

申请日：2013-02-15

Applicant: Xerox Corporation

Inventor： Vladimir Kozitsky ,  Aaron Michael Burry ,  Zhigang Fan ,  Frank Bradley Mayberry ,  John Deppen

IPC: G06K9/00 ,  H04N7/18

CPC classification number: H04N7/18 ,  G06Q10/087 ,  G06Q30/06

Abstract: Images with respect to an object at an ordering, payment, and delivery locations can be captured utilizing an image capturing system. Capture can be after detecting the presence of the object at each location utilizing an object presence sensor. The captured image can be processed to associate it with a signature and can also be processed in order to extract a small region of interest (e.g., license plate) and can be reduced to a unique signature. Signature can be stored into a database together with the corresponding order and images. Signatures can be matched. The order associated with the object matched by the system together with at least one of the images captured at the delivery point and the order point can be displayed at a user interface located at the payment/delivery point to ensure that the right order is delivered to the right customer associated with the object.

Abstract translation: 可以使用图像捕获系统捕获在订购，付款和传送位置处的对象的图像。 在使用对象存在传感器检测每个位置处的对象的存在之后，可以进行捕获。 捕获的图像可以被处理以将其与签名相关联，并且还可以被处理以便提取感兴趣的小区域（例如，牌照），并且可以将其缩小为唯一的签名。 签名可以与相应的订单和图像一起存储到数据库中。 签名可以匹配。 与由系统匹配的对象相关联的订单与在传送点和订单点捕获的至少一个图像可以显示在位于支付/传送点的用户界面上，以确保正确的订单被传送到 与对象关联的正确客户。

公开(公告)号：US09449511B2

公开(公告)日：2016-09-20

申请号：US13975245

申请日：2013-08-23

Applicant: XEROX CORPORATION

Inventor： Eric Gross ,  Aaron Michael Burry ,  Peter Paul

IPC: H04N5/232 ,  G06Q30/00 ,  E04H3/02 ,  G08G1/017 ,  G06K9/00

CPC classification number: G08G1/0175 ,  G06K9/00785

Abstract: A computer-implemented method, system, and computer-readable medium is disclosed for determining a sequence order for vehicles in one or more image frames from an operational video, the operational video acquired from a fixed video camera comprising a field of view associated with a vehicle merge area where upstream traffic from a first lane and upstream traffic from a second lane merge to a single lane. The method can include obtaining operational video from a fixed video camera; detecting, within a region of interest (ROI) of the one or more image frames from the operational video, a first area and a second area in the vehicle merge area using a trained classifier that is trained to detect the first area and the second area; and determining the sequence order of the vehicles based on the first area and the second area that are detected.

Abstract translation: 公开了一种计算机实现的方法，系统和计算机可读介质，用于确定来自操作视频的一个或多个图像帧中的车辆的序列顺序，从固定摄像机获取的操作视频，包括与视频相关联的视场 车辆合并区域，其中来自第一车道的上游车流和来自第二车道的上游车流合并到单车道。 该方法可以包括从固定摄像机获取操作视频; 在运行视频中的一个或多个图像帧的感兴趣区域（ROI）内检测车辆合并区域中的第一区域和第二区域，使用经过训练的训练分类器来检测第一区域和第二区域 ; 以及基于检测到的第一区域和第二区域确定车辆的顺序。

公开(公告)号：US09361690B2

公开(公告)日：2016-06-07

申请号：US14050041

申请日：2013-10-09

Applicant: Xerox Corporation

Inventor： Edgar A. Bernal ,  Aaron Michael Burry

IPC: G06K9/00 ,  G06T7/00 ,  G06Q10/00 ,  G08G1/04 ,  G08G1/065 ,  G08G1/095 ,  G07C11/00 ,  G08G1/015 ,  G08G1/017 ,  G08G1/02 ,  G08G1/042 ,  G08G1/0967

CPC classification number: G06T7/0022 ,  G06Q10/00 ,  G06Q10/06311 ,  G06T2207/10004 ,  G06T2207/30236 ,  G07C11/00 ,  G08G1/015 ,  G08G1/0175 ,  G08G1/02 ,  G08G1/04 ,  G08G1/042 ,  G08G1/065 ,  G08G1/095 ,  G08G1/096716 ,  G08G1/096783

Abstract: A method, non-transitory computer readable medium, and apparatus for side-by-side traffic location load balancing are disclosed. For example, the method receives one or more video images of a side-by-side traffic location, determines a number of cars in a first lane and a number of cars in a second lane of the side-by-side traffic location based upon the one or more video images, calculates a delta between the number of cars in the first lane and the number of cars in the second lane and recommends the first lane or the second lane based upon the delta and a respective weighting factor associated with the first lane and the second lane to provide a load balance of the cars at the side-by-side traffic location.

Abstract translation: 公开了一种并行交通位置负载平衡的方法，非暂时计算机可读介质和装置。 例如，该方法接收并排交通位置的一个或多个视频图像，基于并行交通位置确定第一车道中的轿厢数量和并排交通位置的第二车道中的轿厢数量 所述一个或多个视频图像计算第一车道中的轿厢数量和第二车道中的轿厢数量之间的增量，并且基于增量和与第一车道相关联的相应加权因子推荐第一车道或第二车道 车道和第二车道，以在并排交​​通位置提供汽车的负载平衡。

公开(公告)号：US20150310628A1

公开(公告)日：2015-10-29

申请号：US14261510

申请日：2014-04-25

Applicant: Xerox Corporation

Inventor： Aaron Michael Burry

IPC: G06T7/20

CPC classification number: G06T7/2006 ,  G06T7/246 ,  G06T2207/10016 ,  G06T2207/20081 ,  G06T2207/30236

Abstract: Video-based object tracking accuracy is improved by a tentative identification of objects to be tracked. An identified blob that does not encompass a previously established set of tracking features (“tracker”) triggers initialization of an infant tracker. If that tracker remains the only tracker or becomes the “oldest” tracker associated with a blob identified in subsequent video frames, the “age” of the tracker is increased. If, in subsequent frames, the tracker is encompassed by a blob that is associated with an “older” tracker, the “age” of the tracker is decreased. Infant trackers that reach or exceed a threshold “age” are promoted to adult status. Adult trackers can be processed as being associated with valid objects. Trackers established for blobs identified due to mask segmentation tend not to cause false object detections. When segmentation is corrected, blob segments are combined and redundant trackers for the associated object are demoted and ignored.

Abstract translation: 通过暂时识别要跟踪的对象来改善基于视频的对象跟踪精度。 不包含先前建立的一组跟踪特征（“跟踪器”）的识别的Blob触发婴儿跟踪器的初始化。 如果该跟踪器仍然是唯一的跟踪器，或者成为与随后视频帧中识别的斑点相关联的“最旧”跟踪器，则跟踪器的“年龄”增加。 如果在随后的帧中，跟踪器被与“较旧”跟踪器相关联的斑点包围，则跟踪器的“年龄”减小。 达到或超过阈值“年龄”的婴儿跟踪器被提升为成年人身份。 成人跟踪器可以被处理为与有效对象相关联。 由于掩模分割而识别的斑点建立的跟踪器往往不会导致伪对象检测。 当分段被纠正时，组合段和相关对象的冗余跟踪器被降级和忽略。

公开(公告)号：US09158985B2

公开(公告)日：2015-10-13

申请号：US14195036

申请日：2014-03-03

Applicant: Xerox Corporation

Inventor： Qun Li ,  Edgar A. Bernal ,  Aaron Michael Burry ,  Peter Paul ,  Robert P. Loce

IPC: G06K9/00 ,  G06K9/32 ,  G06T7/00

CPC classification number: G06T7/194 ,  G06K9/00785 ,  G06K9/342 ,  G06K9/4652 ,  G06T7/11 ,  G06T7/174 ,  G06T2207/10016 ,  G06T2207/20112 ,  G06T2207/30232 ,  G06T2207/30236

Abstract: A method for processing an image of a scene of interest includes receiving an original target image of a scene of interest at an image processing device from an image source device, the original target image exhibiting shadowing effects associated with the scene of interest when the original target image was captured, the original target image comprising a plurality of elements and representing an instantaneous state for the scene of interest, pre-processing the original target image using a modification identification algorithm to identify elements of the original target image to be modified, and generating a copy mask with a mask region representing the elements to be modified and a non-mask region representing other elements of the original target image. An image processing device for processing an image of a scene of interest and a non-transitory computer-readable medium are also provided.

Abstract translation: 用于处理感兴趣场景的图像的方法包括：从图像源装置在图像处理装置处接收感兴趣场景的原始目标图像，原始目标图像在原始目标时显示与感兴趣场景相关联的阴影效果 拍摄图像，原始目标图像包括多个元素并表示感兴趣场景的瞬时状态，使用修改识别算法对原始目标图像进行预处理，以识别要修改的原始目标图像的元素，并且生成 具有表示要修改的元素的掩模区域的复制掩模和表示原始目标图像的其他元素的非掩模区域。 还提供了一种用于处理感兴趣场景的图像和非暂时性计算机可读介质的图像处理装置。

公开(公告)号：US20140348392A1

公开(公告)日：2014-11-27

申请号：US13899742

申请日：2013-05-22

Applicant: XEROX CORPORATION

Inventor： Aaron Michael Burry ,  Vladimir Kozitsky

IPC: G06K9/32

CPC classification number: G06K9/325 ,  G06K2209/15

Abstract: Methods and systems for automatically determining the issuing state of a license plate. An image of a license plate acquired by an ALPR engine can be processed via one or more OCR engines such that each OCR engine among the OCR engines is tuned to a particular state. Confidence data output from the OCR engine(s) can be analyzed (among other factors) to estimate the issuing state associated with the license plate. Multiple observations related to the issuing state can be merged to derive an overall conclusion and assign an associated confidence value with respect to the confidence data and determine a likely issuing state associated with the license plate.

Abstract translation: 自动确定车牌发卡状态的方法和系统。 可以通过一个或多个OCR引擎来处理由ALPR引擎获取的车牌的图像，使得OCR引擎中的每个OCR引擎被调谐到特定状态。 可以分析从OCR引擎输出的置信度数据（以及其他因素）来估计与车牌相关的发卡状态。 可以合并与发布状态有关的多个观察结果，以获得总体结论，并且相对于置信度数据分配相关的置信度值，并确定与该牌照相关联的可能发布状态。

公开(公告)号：US20140301606A1

公开(公告)日：2014-10-09

申请号：US13857657

申请日：2013-04-05

Applicant: XEROX CORPORATION

Inventor： Peter Paul ,  Vladimir Kozitsky ,  Aaron Michael Burry ,  Martin Edward Hoover ,  Mark Cantelli

IPC: G06K9/18

CPC classification number: G06K9/2027 ,  G06K9/3258 ,  G06K2209/15

Abstract: Methods, systems, and processor-readable media for data augmentation utilized in an automatic license plate recognition engine. A machine-readable code can be associated with an automatic license plate recognition engine. The machine-readable code can be configured to define parameters that drive processing within the automatic license plate recognition engine to produce recognition results thereof and enhance a machine readability of a license plate recognized and analyzed via the automatic license plate recognition engine.

Abstract translation: 用于在自动车牌识别引擎中使用的用于数据增加的方法，系统和处理器可读介质。 机器可读代码可以与自动车牌识别引擎相关联。 机器可读代码可以被配置为定义驱动自动车牌识别引擎内的处理以产生其识别结果的参数，并提高通过自动车牌识别引擎识别和分析的牌照的机器可读性。

公开(公告)号：US20140270353A1

公开(公告)日：2014-09-18

申请号：US13827222

申请日：2013-03-14

Applicant: XEROX CORPORATION

Inventor： Raja Bala ,  Zhigang Fan ,  Aaron Michael Burry ,  Jose Antonio Rodriguez-Serrano ,  Vishal Monga ,  Xuan Mo

IPC: G06K9/00 ,  G06K9/62

CPC classification number: G06K9/00771 ,  G06K9/6249

Abstract: Methods, systems, and processor-readable media for pruning a training dictionary for use in detecting anomalous events from surveillance video. Training samples can be received, which correspond to normal events. A dictionary can then be constructed, which includes two or more classes of normal events from the training samples. Sparse codes are then generated for selected training samples with respect to the dictionary derived from the two or more classes of normal events. The size of the dictionary can then be reduced by removing redundant dictionary columns from the dictionary via analysis of the sparse codes. The dictionary is then optimized to yield a low reconstruction error and a high-interclass discriminability.

Abstract translation: 用于修剪用于检测来自监视视频的异常事件的训练词典的方法，系统和处理器可读介质。 可以收到培训样本，对应于正常事件。 然后可以构建字典，其包括来自训练样本的两个或更多类的正常事件。 然后针对从两个或多个正常事件类派生的字典为选定的训练样本生成稀疏码。 然后可以通过对稀疏代码的分析从字典中删除冗余字典列来减少字典的大小。 然后对该字典进行优化，以产生低重构误差和高阶间的可辨别性。

公开(公告)号：US20140079315A1

公开(公告)日：2014-03-20

申请号：US13746412

申请日：2013-01-22

Applicant: XEROX CORPORATION

Inventor： Vladimir Kozitsky ,  Aaron Michael Burry ,  Peter Paul

IPC: G06K9/62

CPC classification number: A47C7/14 ,  B60N2/02 ,  B60N2/1803 ,  B60N2/1835 ,  B60N2/1864 ,  B60N2002/0236 ,  G06K9/3258 ,  G06K9/623 ,  G06K9/6267 ,  G06K2009/4666 ,  G06K2209/01 ,  G06K2209/15

Abstract: Methods and systems for reducing the required footprint of SNoW-based classifiers via optimization of classifier features. A compression technique involves two training cycles. The first cycle proceeds normally and the classifier weights from this cycle are used to rank the Successive Mean Quantization Transform (SMQT) features using several criteria. The top N (out of 512 features) are then chosen and the training cycle is repeated using only the top N features. It has been found that OCR accuracy is maintained using only 60 out of 512 features leading to an 88% reduction in RAM utilization at runtime. This coupled with a packing of the weights from doubles to single byte integers added a further 8× reduction in RAM footprint or a reduction of 68× over the baseline SNoW method.

Abstract translation: 通过优化分类器功能来减少基于SNoW的分类器所需占用面积的方法和系统。 压缩技术涉及两个训练周期。 第一个周期正常进行，并且使用来自该周期的分类器权重使用几个标准对连续平均量化变换（SMQT）特征进行排序。 然后选择顶部N（512个特征之​​一），并且仅使用前N个特征重复训练周期。 已经发现，使用仅512个特征中的60个来维持OCR精度，导致运行时RAM利用率降低88％。 这加上权重从双精度到单字节整数的加载，增加了RAM占用的8倍减少或基线SNoW方法减少了68倍。

公开(公告)号：US09418305B1

公开(公告)日：2016-08-16

申请号：US14699289

申请日：2015-04-29

Applicant: Xerox Corporation

Inventor： Palghat S. Ramesh ,  Vladimir Kozitsky ,  Aaron Michael Burry

IPC: G06K9/00 ,  G06K9/32 ,  G06K9/78

CPC classification number: G06K9/3258 ,  G06K9/348 ,  G06K2209/01 ,  G06K2209/15

Abstract: A segmentation free method and system for automatic license plate recognition. An OCR classifier can be swept across an image of a license plate. Characters and their locations can be inferred with respect to the image of the license plate using probabilistic inference based on a Hidden Markov Model (HMM). A language model can be combined with a license plate candidate from the HMM to infer the optimal or best license plate code. The language model can be configured by employing a corpus of license plate codes, wherein the corpus includes a distribution representative of training sets and tests sets.

Abstract translation: 一种自动车牌识别的无分割方法和系统。 OCR分类器可以扫过牌照的图像。 可以使用基于隐马尔可夫模型（HMM）的概率推理，相对于车牌的图像来推断人物及其位置。 语言模型可以与HMM的车牌候选人结合起来推断最佳或最佳的车牌代码。 语言模型可以通过使用车牌代码语料库进行配置，其中语料库包括训练集和测试集的分布代表。