公开(公告)号：US20160253548A1

公开(公告)日：2016-09-01

申请号：US14941273

申请日：2015-11-13

Applicant: QUALCOMM Incorporated

Inventor： Alwyn DOS REMEDIOS ,  Frederick William KIEFER ,  John Keith SCHNEIDER ,  Tao SHENG ,  Fitzgerald JOHN ARCHIBALD ,  Ming LI

IPC: G06K9/00

CPC classification number: G06K9/00093 ,  G06K9/00013 ,  G06K9/00073 ,  G06K9/00087 ,  G06K9/6292

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。

公开(公告)号：US20150347814A1

公开(公告)日：2015-12-03

申请号：US14290408

申请日：2014-05-29

Applicant: QUALCOMM Incorporated

Inventor： Tao SHENG ,  Alwyn DOS REMEDIOS

IPC: G06K9/00 ,  G06K9/46

CPC classification number: G06K9/0061 ,  G06F3/013 ,  G06K9/00604 ,  G06K9/00617 ,  G06K9/00624 ,  G06K9/46 ,  G06K9/4609 ,  G06K2009/4666

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。

公开(公告)号：US20210019652A1

公开(公告)日：2021-01-21

申请号：US16515711

申请日：2019-07-18

Applicant: QUALCOMM Incorporated

Inventor： Serag GADELRAB ,  James ESLIGER ,  Meghal VARIA ,  Kyle ERNEWEIN ,  Alwyn DOS REMEDIOS ,  George LEE

IPC: G06N20/00 ,  G06N5/04 ,  G06F11/34

Abstract: Certain aspects of the present disclosure provide techniques for concurrently performing inferences using a machine learning model and optimizing parameters used in executing the machine learning model. An example method generally includes receiving a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. At least a first inference is performed on the data set using the machine learning model to meet a latency specified for generation of the first inference from receipt of the request. While performing the at least the first inference, operational parameters resulting in inference performance approaching the performance metric targets are identified based on the machine learning model and operational properties of the computing device. The identified operational parameters are applied to performance of subsequent inferences using the machine learning model.

公开(公告)号：US20160034027A1

公开(公告)日：2016-02-04

申请号：US14446169

申请日：2014-07-29

Applicant: QUALCOMM Incorporated

Inventor： Tao SHENG ,  Alwyn DOS REMEDIOS

IPC: G06F3/00 ,  G06T7/00 ,  G06F3/0488 ,  G06F3/041 ,  G06F3/03 ,  G06F3/01

CPC classification number: G06F3/005 ,  G06F3/017 ,  G06F3/0304 ,  G06F3/0416 ,  G06F3/04883 ,  G06F3/04886 ,  G06T7/70 ,  G06T2207/20081

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。

公开(公告)号：US20240112090A1

公开(公告)日：2024-04-04

申请号：US18539022

申请日：2023-12-13

Applicant: QUALCOMM Incorporated

Inventor： Serag GADELRAB ,  James Lyall ESLIGER ,  Meghal VARIA ,  Kyle ERNEWEIN ,  Alwyn DOS REMEDIOS ,  George LEE

IPC: G06N20/00 ,  G06F11/34 ,  G06N5/04

CPC classification number: G06N20/00 ,  G06F11/3466 ,  G06N5/04

Abstract: Certain aspects of the present disclosure provide techniques for concurrently performing inferences using a machine learning model and optimizing parameters used in executing the machine learning model. An example method generally includes receiving a request to perform inferences on a data set using the machine learning model and performance metric targets for performance of the inferences. At least a first inference is performed on the data set using the machine learning model to meet a latency specified for generation of the first inference from receipt of the request. While performing the at least the first inference, operational parameters resulting in inference performance approaching the performance metric targets are identified based on the machine learning model and operational properties of the computing device. The identified operational parameters are applied to performance of subsequent inferences using the machine learning model.

公开(公告)号：US20130272570A1

公开(公告)日：2013-10-17

申请号：US13797579

申请日：2013-03-12

Applicant: QUALCOMM INCORPORATED

Inventor： Tao SHENG ,  Alwyn DOS REMEDIOS

IPC: G06F3/01

CPC classification number: G06F3/017 ,  G06F3/005 ,  G06F3/0484 ,  G06K9/00355 ,  G06T7/20 ,  G06T7/269 ,  G06T2207/20016 ,  G06T2207/20021 ,  G06T2207/20081 ,  G06T2207/30196

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。