Fingerprint Verification System
    1.
    发明申请
    Fingerprint Verification System 有权
    指纹验证系统

    公开(公告)号:US20160253548A1

    公开(公告)日:2016-09-01

    申请号:US14941273

    申请日:2015-11-13

    Abstract: Embodiments of apparatus, computer program product, and method for verifying fingerprint images are disclosed. In one embodiment, a method of verifying fingerprint images includes receiving an inquiry fingerprint image of a user, identifying pattern characteristics of the inquiry fingerprint image, identifying minutiae characteristics of the inquiry fingerprint image, determining a weighted combination of the pattern characteristics of the inquiry fingerprint image and the minutiae characteristics of the inquiry fingerprint image, where the weighted combination comprises a pattern matching weight and a minutiae matching weight derived in accordance with a separation of a first empirical probability density function of genuine fingerprints from a second empirical probability density function of impostor fingerprints, and verifying the inquiry fingerprint image based on a set of fused scores computed using the weighted combination of the pattern characteristics of the inquiry fingerprint image and the minutiae characteristics of the inquiry fingerprint image.

    Abstract translation: 公开了用于验证指纹图像的装置,计算机程序产品和方法的实施例。 在一个实施例中,验证指纹图像的方法包括接收用户的询问指纹图像,识别查询指纹图像的图案特征,识别查询指纹图像的细节特征,确定查询指纹图案特征的加权组合 图像和查询指纹图像的细节特征,其中加权组合包括模式匹配权重和根据真实指纹的第一经验概率密度函数与假冒者的第二经验概率密度函数的分离而导出的细节匹配权重 指纹,以及基于使用询问指纹图像的图案特征和询问指纹图像的细节特征的加权组合计算的一组融合分数来验证查询指纹图像。

    EFFICIENT FOREST SENSING BASED EYE TRACKING
    2.
    发明申请
    EFFICIENT FOREST SENSING BASED EYE TRACKING 有权
    有效的森林感知基于眼睛的追踪

    公开(公告)号:US20150347814A1

    公开(公告)日:2015-12-03

    申请号:US14290408

    申请日:2014-05-29

    Abstract: Methods, systems, computer-readable media, and apparatuses for novel eye tracking methodologies are presented. Specifically, after an initial determination of a person's eyes within a field of view (FOV), methods of the present disclosures may track the person's eyes even with part of the face occluded, and may quickly re-acquire the eyes even if the person's eyes exit the FOV. Each eye may be tracked individually, at a faster rate of eye tracking due to the novel methodology, and successful eye tracking even at low image resolution and/or quality is possible. In some embodiments, the eye tracking methodology of the present disclosures includes a series of sub-tracker techniques, each performing different eye-tracking functions that, when combined, generate a highest-confidence location of where the eye has moved to in the next image frame.

    Abstract translation: 提出了用于新颖的眼睛跟踪方法的方法,系统,计算机可读介质和装置。 具体来说,在视野(FOV)中初步确定了人的眼睛后,即使眼睛的一部分被遮挡,本发明的方法也可以跟踪人的眼睛,即使人的眼睛也可以快速重新获得眼睛 退出FOV。 由于新颖的方法,可以以更快的眼睛跟踪速率单独跟踪每只眼睛,并且即使在低图像分辨率和/或质量下也可以成功地进行眼睛跟踪。 在一些实施例中,本公开的眼睛跟踪方法包括一系列子跟踪器技术,每个子跟踪器技术执行不同的眼睛跟踪功能,当组合时,生成眼睛在下一个图像中移动到哪里的最高置信位置 帧。

    OPTICAL TRACKING OF A USER-GUIDED OBJECT FOR MOBILE PLATFORM USER INPUT
    3.
    发明申请
    OPTICAL TRACKING OF A USER-GUIDED OBJECT FOR MOBILE PLATFORM USER INPUT 审中-公开
    用于移动平台用户输入的用户指导对象的光学跟踪

    公开(公告)号:US20160034027A1

    公开(公告)日:2016-02-04

    申请号:US14446169

    申请日:2014-07-29

    Abstract: A method of receiving user input by a mobile platform includes capturing a sequence of images with a camera of the mobile platform. The sequence of images includes images of a user-guided object in proximity to a planar surface that is separate and external to the mobile platform. The mobile platform then tracks movement of the user-guided object about the planar surface by analyzing the sequence of images. Then the mobile platform recognizes the user input based on the tracked movement of the user-guided object.

    Abstract translation: 由移动平台接收用户输入的方法包括利用移动平台的相机捕获图像序列。 图像序列包括在与移动平台分开且外部的平面表面附近的用户引导对象的图像。 然后,移动平台通过分析图像序列跟踪关于平面表面的用户引导对象的移动。 然后,移动平台基于用户引导对象的跟踪移动识别用户输入。

    DYNAMIC LEARNING FOR OBJECT TRACKING
    4.
    发明申请
    DYNAMIC LEARNING FOR OBJECT TRACKING 有权
    动态跟踪的动态学习

    公开(公告)号:US20150071487A1

    公开(公告)日:2015-03-12

    申请号:US14023883

    申请日:2013-09-11

    Abstract: Techniques described herein relate to mobile computing device technologies, such as systems, methods, apparatuses, and computer-readable media for tracking an object from a plurality of objects. In one aspect, the plurality of objects may be similar. Techniques discussed herein propose dynamically learning information associated with each of the objects and discriminating between objects based on their differentiating features. In one implementation, this may be done by maintaining a database associated with each object and updating the dynamic database transferred while the objects are tracked. The tracker uses algorithmic means for differentiating objects by focusing on the differences amongst the objects. For example, in one implementation, the method may weigh the differences between different fingers higher than their associated similarities to facilitate differentiating the fingers.

    Abstract translation: 本文描述的技术涉及用于跟踪来自多个对象的对象的移动计算设备技术,诸如系统,方法,设备和计算机可读介质。 在一个方面,多个对象可以是类似的。 本文中讨论的技术提出了动态地学习与每个对象相关联的信息,并且基于它们的区分特征来区分对象。 在一个实现中,这可以通过维护与每个对象相关联的数据库并且在跟踪对象时更新所传送的动态数据库来完成。 跟踪器使用算法手段,通过关注对象之间的差异来区分对象。 例如,在一个实施方案中,该方法可以称重不同手指之间的差异高于其相关联的相似度,以便于区分手指。

    ROBUST AND EFFICIENT LEARNING OBJECT TRACKER
    5.
    发明申请
    ROBUST AND EFFICIENT LEARNING OBJECT TRACKER 有权
    坚固有效的学习目标跟踪器

    公开(公告)号:US20130272570A1

    公开(公告)日:2013-10-17

    申请号:US13797579

    申请日:2013-03-12

    Abstract: This disclosure presents methods, systems, computer-readable media, and apparatuses for optically tracking the location of one or more objects. The techniques may involve accumulation of initial image data, establishment of a dataset library containing image features, and tracking using a plurality of modules or trackers, for example an optical flow module, decision forest module, and color tracking module. Tracking outputs from the optical flow, decision forest and/or color tracking modules are synthesized to provide a final tracking output. The dataset library may be updated in the process.

    Abstract translation: 本公开提供了用于光学跟踪一个或多个对象的位置的方法,系统,计算机可读介质和装置。 这些技术可以包括初始图像数据的累积,包含图像特征的数据集库的建立以及使用多个模块或跟踪器(例如光流模块,决策林模块和颜色跟踪模块)的跟踪。 来自光流,决策树和/或颜色跟踪模块的跟踪输出被合成以提供最终跟踪输出。 数据集库可能会在此过程中更新。

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