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    • 15. 发明申请
    • ALARM SOLUTION FOR SECURING SHOPPING CHECKOUT
    • 报警解决方案,用于安全购物
    • US20090237232A1
    • 2009-09-24
    • US12052046
    • 2008-03-20
    • Jonathan H. Connell IIMyron D. FlicknerNorman HaasArun HampapurSharathchandra U. Pankanti
    • Jonathan H. Connell IIMyron D. FlicknerNorman HaasArun HampapurSharathchandra U. Pankanti
    • G08B19/00
    • G08B13/00G06Q20/203G06Q20/209G08B13/246
    • Under the present invention, a single, overall alarm for an entire set of shopping items will be used for any and all discrepancies. The metric used for creating an alarm for the overall set of shopping items can be based on any one of the following candidate policies: if at least one item generated an alarm; if some fixed number of items generated an alarm; if some threshold discrepancy metric got exceed; if basket size is larger than certain threshold cash value and the alarm exceeded certain threshold alarm rate; a randomly generated alarm (e.g., random audit); the customer's identity and track record (e.g., loyalty card); and/or any combination of the above. Regardless, if an overall alarm is generated one or more of the following actions can be taken: no action send the customer to customer service; appropriately record customer track record (e.g., loyalty card) when customer identity is available; audit the customer at the “shop exit; and/or any combination of thereof.
    • 在本发明中,对于整个购物项目的单个整体报警将用于任何和所有差异。 用于为整个购物项目创建警报的度量可以基于以下任一候选策略:如果至少一个项目产生了警报; 如果有固定数量的物品产生报警; 如果一些阈值差异度量超过了; 如果篮子尺寸大于某个门槛现金值,并且报警超过一定阈值报警率; 随机生成的警报(例如,随机审计); 客户的身份和记录(例如会员卡); 和/或上述的任何组合。 无论如何,如果发生整体报警,可采取以下一项或多项措施:无需向客户提供任何行动; 当客户身份可用时,适当地记录客户记录(例如会员卡); 在“商店出口”处审核客户;和/或其任何组合。
    • 19. 发明授权
    • Secure self-checkout
    • 安全自助结帐
    • US08746557B2
    • 2014-06-10
    • US12037266
    • 2008-02-26
    • Jonathan H. Connell, IINorman HaasSharathchandra U. Pankanti
    • Jonathan H. Connell, IINorman HaasSharathchandra U. Pankanti
    • G06K15/00
    • A47F9/047G06K9/6215G06Q30/00G07G1/0063G07G3/003
    • Under the present invention, item verification is automated and expedited. Specifically, items to be purchased can be scanned by the shopper using a barcode reader (e.g., a scanner) attached to or positioned near the shopping receptacle. As items are scanned, they are identified based on their barcode and added to an item list. Item verification can then performed at checkout using imaging technology. For example, the shopping cart or shopping basket can be brought into the field of view of a computer-connected camera. The camera and computer can, working from the customer's item list developed when the items are scanned, observe each product in the receptacle and “ring it up”. If all products can be accounted for, the customer is free to leave; otherwise the customer is denied egress, informed of the problem, etc. A store employee can also be signaled to investigate. The total time required to make the decision is the time to take a picture and process it, which by human standards is very fast; faster than existing verification methods.
    • 在本发明中,项目验证是自动化和加速的。 特别地,购物者可以使用附接到购物容器附近或位于购物容器附近的条形码读取器(例如,扫描器)来扫描要购买的物品。 当项目被扫描时,它们根据其条形码被识别并被添加到项目列表中。 然后可以使用成像技术在结帐时执行项目验证。 例如,购物车或购物篮可以被带入计算机连接的相机的视野中。 照相机和计算机可以在扫描物品时开发的客户项目列表中进行操作,观察插座中的每个产品并“振铃”。 如果所有产品都可以核算,客户可以自由离开; 否则客户被拒绝出境,通知问题等。店员也可以被告知调查。 作出决定所需的总时间是拍摄照片和处理时间,人体标准非常快; 比现有的验证方法快。
    • 20. 发明授权
    • Anomaly detection in images and videos
    • 图像和视频中的异常检测
    • US08724904B2
    • 2014-05-13
    • US13280896
    • 2011-10-25
    • Yuichi FujikiNorman HaasYing LiCharles A. OttoBalamanohar PaluriSharathchandra Pankanti
    • Yuichi FujikiNorman HaasYing LiCharles A. OttoBalamanohar PaluriSharathchandra Pankanti
    • G06K9/46
    • G06K9/6284B61L23/044B61L23/047B61L23/048G06K9/6218
    • A system, method, and computer program product for detecting anomalies in an image. In an example embodiment the method includes partitioning each image of a set of images into a plurality of image local units. The method further includes clustering all local units in the image set into clusters, and consequently assigning a class label to each local unit based on the clustering results. The local units with identical class labels having at least one substantially related image feature. Further, the method includes assigning a weight to each of the local units based on a variation of the class labels across all images in a set of images. The method further includes performing a clustering over all images in the set by using a distance metric that takes the learned weight of each local unit into account, then determining the images that belong to minorities of the clusters as anomalies.
    • 一种用于检测图像异常的系统,方法和计算机程序产品。 在示例实施例中,该方法包括将一组图像的每个图像划分为多个图像本地单元。 该方法还包括将图像集中的所有局部单元聚类成群集,并且因此基于聚类结果将类标签分配给每个本地单元。 具有相同类别标签的本地单元具有至少一个基本上相关的图像特征。 此外,该方法包括基于一组图像中的所有图像上的类别标签的变化来为每个本地单元分配权重。 该方法还包括通过使用考虑每个本地单元的学习权重的距离度量来执行集合中的所有图像的聚类,然后将属于集群的少数群体的图像确定为异常。