SYSTEM AND METHOD FOR VIDEO-BASED DETECTION OF DRIVE-AROUNDS IN A RETAIL SETTING
    11.
    发明申请
    SYSTEM AND METHOD FOR VIDEO-BASED DETECTION OF DRIVE-AROUNDS IN A RETAIL SETTING 有权
    用于零售设备中基于视频检测驱动器的系统和方法

    公开(公告)号:US20150310459A1

    公开(公告)日:2015-10-29

    申请号:US14280863

    申请日:2014-05-19

    CPC classification number: G06Q30/0201

    Abstract: A system and method for detection of drive-arounds in a retail setting. An embodiment includes acquiring images of a retail establishment, analyzing the images to detect entry of a customer onto the premises of the retail establishment, tracking a detected customer's location as the customer traverses the premises of the retail establishment, analyzing the images to detect exit of the detected customer from the premises of the retail establishment, and generating a drive-around notification if the customer does not enter a prescribed area or remain on the premises of the retail location for at least a prescribed minimum period of time.

    Abstract translation: 用于在零售环境中检测驱动器的系统和方法。 一个实施例包括获取零售店的图像,分析图像以检测客户进入零售店的房屋,在客户穿过零售店的房屋时跟踪检测到的客户的位置,分析图像以检测出 检测到的客户从零售店的房屋,并且如果客户不进入规定区域或者在零售地点的房屋内停留至少规定的最短时间段,则产生驱动通知。

    SYSTEM AND METHOD FOR VIDEO-BASED DETECTION OF GOODS RECEIVED EVENT IN A VEHICULAR DRIVE-THRU
    12.
    发明申请
    SYSTEM AND METHOD FOR VIDEO-BASED DETECTION OF GOODS RECEIVED EVENT IN A VEHICULAR DRIVE-THRU 审中-公开
    用于基于视觉检测的车辆接收事件的系统和方法

    公开(公告)号:US20150310365A1

    公开(公告)日:2015-10-29

    申请号:US14289683

    申请日:2014-05-29

    CPC classification number: G06Q10/0639 G06K9/00771 G06K9/3233 G06Q10/063

    Abstract: A system and method for detection of a goods-received event includes acquiring images of a retail location including a vehicular drive-thru, determining a region of interest within the images, the region of interest including at least a portion of a region in which goods are delivered to a customer, and analyzing the images using at least one computer vision technique to determine when goods are received by a customer. The analyzing includes identifying at least one item belonging to a class of items, the at least one item's presence in the region of interest being indicative of a goods-received event.

    Abstract translation: 用于检测商品接收事件的系统和方法包括获取零售位置的图像,所述图像包括车辆驱动通过,确定图像内的感兴趣区域,所述感兴趣区域包括货物的区域的至少一部分 交付给客户,并使用至少一种计算机视觉技术来分析图像,以确定货物何时被客户接收。 所述分析包括识别属于一类项目的至少一个项目,所述至少一个项目在所述感兴趣区域中的存在是指示商品接收事件。

    Heuristic-based approach for automatic payment gesture classification and detection
    13.
    发明授权
    Heuristic-based approach for automatic payment gesture classification and detection 有权
    用于自动支付手势分类和检测的基于启发式的方法

    公开(公告)号:US09165194B2

    公开(公告)日:2015-10-20

    申请号:US13964652

    申请日:2013-08-12

    Abstract: A system and method for automatic classification and detection of a payment gesture are disclosed. The method includes obtaining a video stream from a camera placed above at least one region of interest, the region of interest classifying the payment gesture. A background image is generated from the obtained video stream. Motion is estimated in at least two consecutive frames from the video stream. A representation is created from the background image and the estimated motion occurring within the at least one region of interest. The payment gesture is detected based on the representation.

    Abstract translation: 公开了一种用于自动分类和检测支付手势的系统和方法。 该方法包括从放置在至少一个感兴趣区域上的相机获取视频流,该感兴趣区域对支付手势进行分类。 从获得的视频流生成背景图像。 从视频流中至少连续两帧估计运动。 从背景图像和在所述至少一个感兴趣区域内发生的估计运动创建表示。 基于表示检测支付手势。

    METHOD AND APPARATUS FOR COMPRESSIVE IMAGING OF A SCENE USING A SINGLE PIXEL CAMERA
    14.
    发明申请
    METHOD AND APPARATUS FOR COMPRESSIVE IMAGING OF A SCENE USING A SINGLE PIXEL CAMERA 有权
    使用单像素摄像机对场景进行压缩成像的方法和装置

    公开(公告)号:US20150281543A1

    公开(公告)日:2015-10-01

    申请号:US14227595

    申请日:2014-03-27

    CPC classification number: H03M7/3062 H04N5/2254 H04N5/238

    Abstract: A method, non-transitory computer readable medium, and apparatus for compressive imaging of a scene in a single pixel camera are disclosed. For example, the method moves a pseudo-random pattern media behind an aperture until a pseudo-random sampling function of a plurality of pseudo-random sampling functions is viewable through the aperture, records a value of an intensity of a modulated light from the scene with a detector, wherein the intensity of the modulated light is representative of an inner product between the pseudo-random sampling function and an image of the scene and repeats the moving and the recording until a necessary number of a plurality of inner products are processed.

    Abstract translation: 公开了一种用于单个像素摄像机中的场景的压缩成像的方法,非暂时计算机可读介质和装置。 例如,该方法在孔的后方移动伪随机图案介质,直到通过孔径可以看到多个伪随机取样函数的伪随机采样函数,记录来自场景的调制光的强度值 具有检测器,其中调制光的强度表示伪随机采样函数和场景图像之间的内积,并重复移动和记录,直到处理了多个内积的必要数量。

    LOAN RISK ASSESSMENT USING CLUSTER-BASED CLASSIFICATION FOR DIAGNOSTICS
    15.
    发明申请
    LOAN RISK ASSESSMENT USING CLUSTER-BASED CLASSIFICATION FOR DIAGNOSTICS 审中-公开
    贷款风险评估使用基于群集的分类用于诊断

    公开(公告)号:US20150269669A1

    公开(公告)日:2015-09-24

    申请号:US14221944

    申请日:2014-03-21

    CPC classification number: G06Q40/025

    Abstract: Presented are a system, method, and apparatus for loan risk assessment by assignment of a specific loan account to a loan cluster of a plurality of loan clusters. A computing device receives plurality of loan account histories describing a plurality of loan accounts during a training phase. An appropriate supervised classification method is applied to the loan account histories to obtain a mathematical description of loan cluster set. Next, the computing device receives a test loan account payment history describing a test loan account to be analyzed. The test loan account is assigned to at least one cluster of the previously trained cluster set. One or a plurality of causes is then determined for assigning the test loan account to the cluster set; and a predicted risk value for the test loan account is determined based on the cluster the test loan account is assigned to.

    Abstract translation: 提出了贷款风险评估的制度,方法和手段,通过将特定贷款账户分配给多个贷款集群的贷款集群。 计算设备在训练阶段接收描述多个贷款账户的多个贷款账户历史。 将适当的监督分类方法应用于贷款账户历史,以获得贷款集群集的数学描述。 接下来,计算设备接收描述待分析的测试贷款账户的测试贷款账户支付历史。 测试贷款帐户被分配给以前训练过的群集的至少一个群集。 然后确定一个或多个原因用于将测试贷款帐户分配给群集; 并且基于分配了测试贷款账户的集群来确定测试贷款账户的预测风险值。

    Method and apparatus for automated inventory management using depth sensing
    16.
    发明授权
    Method and apparatus for automated inventory management using depth sensing 有权
    使用深度感测自动库存管理的方法和装置

    公开(公告)号:US09015072B2

    公开(公告)日:2015-04-21

    申请号:US13970371

    申请日:2013-08-19

    CPC classification number: G06Q10/087

    Abstract: A method, non-transitory computer readable medium, and apparatus for managing inventory are disclosed. For example, the method monitors a region of interest to determine an inventory level based upon a depth image captured by a depth sensing device, calculates a change in a depth in the region of interest from the depth image that is captured and determines a change in the inventory level associated with the change in the depth of the region of interest.

    Abstract translation: 公开了一种用于管理库存的方法,非暂时性计算机可读介质和装置。 例如,该方法基于由深度感测装置拍摄的深度图像来监视感兴趣区域以确定库存水平,从捕获的深度图像计算感兴趣区域中的深度的变化,并且确定 与感兴趣区域深度变化相关的库存水平。

    ROBUST AND COMPUTATIONALLY EFFICIENT VIDEO-BASED OBJECT TRACKING IN REGULARIZED MOTION ENVIRONMENTS
    17.
    发明申请
    ROBUST AND COMPUTATIONALLY EFFICIENT VIDEO-BASED OBJECT TRACKING IN REGULARIZED MOTION ENVIRONMENTS 有权
    在经常运行的环境中稳健和有计划地进行基于视频的物体跟踪

    公开(公告)号:US20150063628A1

    公开(公告)日:2015-03-05

    申请号:US14017360

    申请日:2013-09-04

    CPC classification number: G06K9/00771

    Abstract: A method and system for video-based object tracking includes detecting an initial instance of an object of interest in video captured of a scene being monitored and establishing a representation of a target object from the initial instance of the object. The dominant motion trajectory characteristic of the target object are then determined and a frame-by-frame location of the target object can be collected in order to track the target object in the video.

    Abstract translation: 一种用于基于视频的对象跟踪的方法和系统包括:检测被捕获的场景的视频的感兴趣对象的初始实例,并从对象的初始实例建立目标对象的表示。 然后确定目标对象的主要运动轨迹特征,并且可以收集目标对象的逐帧位置,以便跟踪视频中的目标对象。

    SINGLE CAMERA VIDEO-BASED SPEED ENFORCEMENT SYSTEM WITH A SECONDARY AUXILIARY RGB TRAFFIC CAMERA
    18.
    发明申请
    SINGLE CAMERA VIDEO-BASED SPEED ENFORCEMENT SYSTEM WITH A SECONDARY AUXILIARY RGB TRAFFIC CAMERA 有权
    单相摄像机视频基础速度执行系统与二次辅助RGB交通摄像机

    公开(公告)号:US20140267733A1

    公开(公告)日:2014-09-18

    申请号:US13795744

    申请日:2013-03-12

    CPC classification number: G08G1/054 G08G1/0175

    Abstract: When performing video-based speed enforcement a main camera and a secondary RGB traffic camera are employed to provide improved accuracy of speed measurement and improved evidentiary photo quality compared to single camera approaches. The RGB traffic camera provides sparse secondary video data at a lower cost than a conventional stereo camera. The sparse stereo processing is performed using the main camera data and the sparse RGB camera data to estimate a height of one or more tracked vehicle features, which in turn is used to improve speed estimate accuracy. By using secondary video, spatio-temporally sparse stereo processing is enabled specifically for estimating the height of a vehicle feature above the road surface.

    Abstract translation: 当执行基于视频的速度执行时,与单个摄像机方法相比,使用主摄像机和次要RGB业务摄像机来提供改进的速度测量精度和改进的证据照片质量。 RGB传输相机以比传统立体相机低的成本提供稀疏的次要视频数据。 使用主相机数据和稀疏RGB相机数据来执行稀疏立体声处理,以估计一个或多个跟踪的车辆特征的高度,其又用于提高速度估计精度。 通过使用次级视频,专门用于估计路面上方的车辆特征的高度的时空稀疏立体声处理。

    HETEROGENEOUS RESOURCE ALLOCATION FOR AUTOMATIC RISK TARGETING AND ACTION PRIORITIZATION IN LOAN MONITORING APPLICATIONS

    公开(公告)号:US20170255996A1

    公开(公告)日:2017-09-07

    申请号:US15062815

    申请日:2016-03-07

    CPC classification number: G06Q40/025

    Abstract: A system, method, and apparatus for determining risk associated with a plurality of loan accounts, having an off-line mode and an online mode. In the off-line mode a first plurality of account histories is received. A maximum value variable m is set. A definition is received of a predetermined maximum look-ahead timeframe p. An iterative variable i is set equal to zero. While i is less than the maximum value variable m, a plurality of variables associated with an account history equaling the iterative variable i are stored and i incremented by 1. A predictive multi-output risk model is trained. In the online mode, a second plurality of account histories is received. A determination is made which accounts have a future risk level greater than a current risk level, and a further determination made which accounts currently require one or more tasks. Accounts requiring tasks are automatically assigned.

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