公开(公告)号：US09218660B2

公开(公告)日：2015-12-22

申请号：US14208941

申请日：2014-03-13

Applicant: Southwest Research Institute

Inventor： John T. Carrola, Jr. ,  Warren Carl Couvillion, Jr. ,  Susan M. Porter ,  David R. Chambers ,  Christopher J. Guerra

IPC: G06K9/00 ,  G06T7/00 ,  G01L1/06 ,  G01L1/24 ,  G01B11/16 ,  H04N5/33 ,  G06T7/60 ,  G06K9/46 ,  G06K9/62

CPC classification number: G06T7/0012 ,  A61B34/10 ,  G01B11/168 ,  G01L1/06 ,  G01L1/241 ,  G01L1/248 ,  G01N21/21 ,  G01N21/23 ,  G01N21/55 ,  G01N2021/557 ,  G06F3/011 ,  G06K9/00624 ,  G06K9/4642 ,  G06K9/6267 ,  G06T7/60 ,  G09B23/28 ,  H04N5/33

Abstract: A method and system for analysis of a viscoelastic response in a deformable material. The system includes a light source configured to provide linearly polarized light and a polariscope configured to receive said linearly polarized light and to generate an image associated with a viscoelastic response of said deformable material. The system also includes a machine vision system configured to operate on the image to locate the response on the deformable material and to classify the response as one of a plurality of predefined types of responses. A display may then be provide that is configured to provide feedback of the location of the viscoelastic response and classification of the response to a user of said system.

Abstract translation: 用于分析可变形材料中的粘弹性响应的方法和系统。 该系统包括被配置为提供线性偏振光的光源和被配置为接收所述线偏振光并且产生与所述可变形材料的粘弹性响应相关联的图像的偏光镜。 该系统还包括机器视觉系统，其被配置为在图像上操作以定位可变形材料上的响应并将响应分类为多种预定类型的响应之一。 然后可以提供被配置为提供粘弹性响应的位置的反馈和对所述系统的用户的响应的分类的显示。

公开(公告)号：US10445930B1

公开(公告)日：2019-10-15

申请号：US15982691

申请日：2018-05-17

Applicant: Southwest Research Institute

Inventor： Kase J. Saylor ,  Daniel P. Nicolella ,  David R. Chambers ,  Travis D. Eliason ,  Donald R. Poole

IPC: G06T7/292 ,  G06T7/80 ,  G06T17/20 ,  G06T7/246

Abstract: A method of using a learning machine to provide a biomechanical data representation of a subject based on markerless video motion capture. The learning machine is trained with both markerless video and marker-based (or other worn body sensor) data, with the marker-based or body worn sensor data being used to generate a full biomechanical model, which is the “ground truth” data. This ground truth data is combined with the markerless video data to generate a training dataset.

公开(公告)号：US10235629B2

公开(公告)日：2019-03-19

申请号：US14732002

申请日：2015-06-05

Applicant: Southwest Research Institute

Inventor： Stephan J. Lemmer ,  David R. Chambers

IPC: G06N7/00 ,  G06K9/62 ,  G06N3/12 ,  G06N99/00 ,  G06K9/00

Abstract: A method and system is provided for estimation of sensor data confidence based on statistical analysis of different classifier and feature-set (CF) configurations. A method may include: training a classifier of a CF configuration based on a training set of nominal sensor data values; executing the classifier on the training set to generate a first set of confidence values; collecting statistics on the confidence values; calculating a confidence decision threshold based on the collected statistics; executing the classifier on an evaluation set of nominal and degraded sensor data values, to generate a second set of confidence values; deciding whether the sensor data values of the evaluation set are nominal or degraded based on a comparison of the second set of confidence values to the confidence decision threshold; and calculating a score to evaluate the trained classifier based on a verification of the decisions.