公开(公告)号：US20150054957A1

公开(公告)日：2015-02-26

申请号：US13975245

申请日：2013-08-23

Applicant: XEROX CORPORATION

Inventor： Eric Gross ,  Aaron Michael Burry ,  Peter Paul

IPC: 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：US20140348391A1

公开(公告)日：2014-11-27

申请号：US13899705

申请日：2013-05-22

Applicant: XEROX CORPORATION

Inventor： Stuart Schweid ,  Aaron Michael Burry ,  Vladimir Kozitsky

IPC: G06K9/00 ,  G06K9/62

CPC classification number: G06K9/623

Abstract: Methods, systems and processor-readable media for determining, post training, which locations of a classifier window are most significant in discriminating between class and non-class objects. The important locations can be determined by calculating the mean and standard deviation of every pixel location in the classifier context for both the positive and negative samples of the classifier. Using a combination of t-scores and mean differences, the importance of all pixel locations in the classifier score can be rank ordered. A sufficient number of pixel locations can then be selected to achieve a detection rate close enough to the full classifier for a particular application.

Abstract translation: 用于确定后期训练的方法，系统和处理器可读介质，分类器窗口的哪些位置在区分类和非类对象之间最显着。 可以通过计算分类器的正和负样本的分类器上下文中每个像素位置的平均值和标准偏差来确定重要位置。 使用t分和平均差的组合，分类器得分中所有像素位置的重要性可以是排序的。 然后可以选择足够数量的像素位置，以实现足够接近特定应用的全分类器的检测率。

公开(公告)号：US20140328518A1

公开(公告)日：2014-11-06

申请号：US13887541

申请日：2013-05-06

Applicant: Xerox Corporation

Inventor： Vladimir Kozitsky ,  Peter Paul ,  Aaron Michael Burry

IPC: G06K9/00

CPC classification number: G06K9/2018 ,  G06K15/021 ,  G06K2209/15 ,  G06K2215/0082 ,  G08G1/0175

Abstract: Methods, systems and processor-readable media for providing a license plate overlay decal with an infrared readable annotation mark for an optical character recognition and segmentation. The annotation mark with respect to character image of a license plate can be designed by training an ALPR engine to improve automatic license plate recognition performance. A plate overlay decal can be rendered with the annotation mark and attached to a license plate. The annotation mark can also be directly placed on the license plate when the license plate is rendered. The annotation mark is visible when illuminated by an infrared light and the license plate appears normal in visible light. The annotation mark enables an ALPR imaging system to obtain more information for each character and utilize the information to improve conclusion accuracy.

Abstract translation: 方法，系统和处理器可读介质，用于提供用于光学字符识别和分割的红外可读注释标记的牌照覆盖贴花。 关于车牌字符图像的注解标记可以通过训练一个ALPR引擎来提高车牌自动识别性能来设计。 可以使用注释标记渲染板覆盖贴花并附加到牌照。 当车牌被渲染时，注解标记也可以直接放置在车牌上。 注意标志在被红外线照射时可见，并且牌照在可见光下显示正常。 注释标记使得ALPR成像系统可以获得每个角色的更多信息，并利用该信息来提高结论准确性。

公开(公告)号：US20130141586A1

公开(公告)日：2013-06-06

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: 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 asscoiated 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递送点和订单点处捕获的图像中的至少一个可以显示在位于支付/交付点的用户界面，以确保正确的订单被传送到 正确的客户反映了对象。