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    • 4. 发明申请
    • System and method for analyzing video from non-static camera
    • 用于分析非静态摄像机视频的系统和方法
    • US20060159308A1
    • 2006-07-20
    • US11039497
    • 2005-01-20
    • Arun HampapurSharathchandra PankantiAndrew Senior
    • Arun HampapurSharathchandra PankantiAndrew Senior
    • G06K9/00G06K9/32
    • H04N7/185G06T3/4038G06T7/246G08B13/19608G08B13/19663
    • A novel system and method of treating the output of moving cameras, in particular ones that enable the application of conventional “static camera” algorithms, e.g., to enable the continuous vigilance of computer surveillance technology to be applied to moving cameras that cover a wide area. According to the invention, a single camera is deployed to cover an area that might require many static cameras and a corresponding number of processing units. A novel system for processing the main video sufficiently enables long-term change detection, particularly the observation that a static object has been moved or has appeared, for instance detecting the parking and departure of vehicles in a parking lot, the arrival of trains in stations, delivery of goods, arrival and dispersal of people, or any other application.
    • 一种处理移动摄像机的输出的新型系统和方法,特别是能够应用常规“静态摄像机”算法的系统和方法,例如,能够将计算机监视技术的持续警觉性应用于覆盖广域的移动摄像机 。 根据本发明,单个相机被部署以覆盖可能需要许多静态相机和相应数量的处理单元的区域。 用于处理主视频的新型系统充分实现长期变化检测,特别是静态物体已被移动或已经出现的观察,例如检测停车场中车辆的停车和离开,列车到达车站 货物的运送,人员的到达和分散,或任何其他的应用程序。
    • 5. 发明申请
    • System and method for remote self-enrollment in biometric databases
    • 用于生物识别数据库远程自动注册的系统和方法
    • US20050229007A1
    • 2005-10-13
    • US10818317
    • 2004-04-06
    • Rudolf BolleSharathchandra PankantiNalini RathaAndrew Senior
    • Rudolf BolleSharathchandra PankantiNalini RathaAndrew Senior
    • G06F21/00G06K9/00
    • G06F21/32G06K9/00G06K9/00885
    • A method and system is provided to provide enrollment of biometric data from individuals without the need for the enrollees to travel to a central location. The system and method provides for optionally detecting multiple types of biometric data, for example, fingerprints, facial scan, visual scan, iris scan, voice scan, or the like, to be captured at the point of enrollee use. During the biometric capture process, the biometric enrollment device monitors and establishes the identity of the enrollee and measures the quality of the biometric input as it occurs. If unacceptable quality is detected, then repeated biometric scans may be necessary, but is done at time of enrollment avoiding any need to send inaccurate information back to a service institution. When the enrollment process completes, the biometric data is encrypted, time stamped and either mailed back to the service institution or is transmitted back. The biometric device may remain with the user for subsequent use as an identification sensor which may authenticate a user with stored biometric information to authenticate a user's identity for a transaction or a request to access a service or equipment. The biometric enrollment device may also be embodied with another piece of equipment to authenticate use of that equipment.
    • 提供了一种方法和系统,用于提供来自个体的生物特征数据的登记,而不需要参加者前往中心位置。 该系统和方法提供了可选地检测多个类型的生物特征数据,例如指纹,面部扫描,视觉扫描,虹膜扫描,语音扫描等,以便在登记者使用时被捕获。 在生物识别捕获过程中,生物识别注册设备监控并建立登记者的身份,并在其发生时测量生物特征输入的质量。 如果检测到不可接受的质量,则可能需要重复的生物特征扫描,但是在注册时完成,避免任何需要向服务机构发送不准确的信息。 当注册过程完成时,生物特征数据被加密,加盖时间戳,并邮寄回服务机构或被传回。 该生物测定装置可以与用户一起留作用作随后用作识别传感器的识别传感器,其可以使用存储的生物特征信息来认证用户身份以进行交易或访问服务或设备的请求。 生物识别登记装置还可以用另一件设备来体现以认证该设备的使用。
    • 7. 发明授权
    • Optimizing the detection of objects in images
    • 优化图像中物体的检测
    • US09235766B2
    • 2016-01-12
    • US13277936
    • 2011-10-20
    • Ying LiSharathchandra Pankanti
    • Ying LiSharathchandra Pankanti
    • G06K9/00
    • G06K9/00805B60W2550/10B60W2550/402G06K9/00818G06T7/70G06T2207/30261H04N5/2256H04N5/2354H04N7/185
    • A system and method detect objects in a digital image. At least positional data associated with a vehicle is received. Geographical information associated with the positional data is received. A probability of detecting a target object within a corresponding geographic area associated with the vehicle is determined based on the geographical data. The probability is compared to a given threshold. An object detection process is at least one of activated and maintained in an activated state in response to an object detection process in response to the probability being one of above and equal to the given threshold. The object detection process detects target objects within at least one image representing at least one frame of a video sequence of an external environment. The object detection process is at least one of deactivated and maintained in a deactivated state in response to the probability being below the given threshold.
    • 系统和方法检测数字图像中的对象。 至少接收到与车辆相关联的位置数据。 接收与位置数据相关联的地理信息。 基于地理数据确定检测与车辆相关联的相应地理区域内的目标对象的概率。 将概率与给定阈值进行比较。 对象检测处理是响应于上述等于给定阈值的概率而响应于对象检测处理而被激活并保持在激活状态中的至少一个。 对象检测处理检测表示外部环境的视频序列的至少一帧的至少一个图像内的目标对象。 响应于低于给定阈值的概率,对象检测处理是去激活和维持在去激活状态中的至少一个。
    • 8. 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。
    • 10. 发明授权
    • Detection of objects in digital images
    • 检测数字图像中的物体
    • US08509526B2
    • 2013-08-13
    • US13086023
    • 2011-04-13
    • Norman HaasYing LiSharathchandra Pankanti
    • Norman HaasYing LiSharathchandra Pankanti
    • G06K9/00
    • G06K9/00818G06K9/6257
    • A system and method to detect objects in a digital image. At least one image representing at least one frame of a video sequence is received. A given color channel of the image is extracted. At least one blob that stands out from a background of the given color channel is identified. One or more features are extracted from the blob. The one or more features are provided to a plurality of pre-learned object models each including a set of pre-defined features associated with a pre-defined blob type. The one or more features are compared to the set of pre-defined features. The blob is determined to be of a type that substantially matches a pre-defined blob type associated with one of the pre-learned object models. At least a location of an object is visually indicated within the image that corresponds to the blob.
    • 一种用于检测数字图像中的对象的系统和方法。 接收表示视频序列的至少一帧的至少一个图像。 提取图像的给定颜色通道。 识别从给定颜色通道的背景中突出出的至少一个斑点。 从斑点中提取一个或多个特征。 将一个或多个特征提供给多个预先学习的对象模型,每个预先学习的对象模型包括与预定义的斑点类型相关联的一组预定义特征。 将一个或多个特征与一组预定义特征进行比较。 blob被确定为与预先识别的对象模型之一相关联的预定义blob类型的类型。 至少一个对象的位置在对应于斑点的图像内被目视指示。