This poster was presented at the 2012 CERIAS poster session. The purpose of this study is to use the Microsoft ® Kinect™ to capture body point data in order to semiautomatically code the metrics for the Human Biometric Sensor Interaction model. Understanding interaction failures by the subject, and providing them feedback can increase overall system performance. We have developed a methodology for using the Microsoft® Kinect™ to facilitate data collection for the HBSI model.

1. Human Biometric Sensor Interaction Model v3.0 -
Kinect
Craig Hebda, Rob Pingry, Weng Kwong Chan, Brent Shuler, Daniel Obot, Michael Texeira, Jay Peters, Kevin O’Connor,
Jacob Hasslegren, Stephen Elliott
Overview
• The purpose of this study is to use the Microsoft ® Kinect™ to capture body point data in order to semi-
3 automatically code the metrics for the Human Biometric Sensor Interaction model. Understanding interaction
failures by the subject, and providing them feedback can increase overall system performance. We have
HBSI
developed a methodology for using the Microsoft® Kinect™ to facilitate data collection for the HBSI model.
HBSI Model Example definition: Slouching Coding
Source: http://www.whatsyourdigitaliq.com/ces‐
Source: preshow‐my‐quick‐takeaway‐from‐
Source: http://msdn.microsoft.com/en‐ http://www.genbetadev.com/herramientas/disponible‐el‐ ballmer%E2%80%99s‐keynote‐at‐ces/
us/library/hh438998.aspx sdk‐de‐kinect‐para‐desarrollar‐nuestras‐propias‐
aplicaciones‐usando‐los‐sensores
•Tracking Points to be used:
•Shoulder_Right
•Shoulder_Left
•Shoulder_Center
•Head
•Spine
•Hip_Center
•Hip_Right
•Hip_Left
HipCenter: [199,176,1.909048]
Spine: [199,167,1.99789]
ShoulderCenter: [203,101,2.132623]
Head: [204,77,2.195843]
ShoulderLeft: [176,122,2.035151]
ElbowLeft: [153,165,1.950089]
WristLeft: [145,203,1.793355]
HandLeft: [145,207,1.77044]
ShoulderRight: [228,122,2.06104]
ElbowRight: [245,166,1.959428]
•Left Slouching: WristRight: [248,204,1.797179]
HandRight: [248,213,1.768724]
•Left shoulder will be lower HipLeft: [186,189,1.857644]
then the right shoulder. KneeLeft: [173,260,1.771513]
AnkleLeft: [183,330,1.740713]
•All points on left arm will be FootLeft: [185,348,1.650042]
HipRight: [211,188,1.893446]
lower then base image. KneeRight: [220,258,1.779559]
AnkleRight: [213,333,1.671088]
•Head will be tilted to left. FootRight: [215,349,1.570665]
-----------------------------------
•Left hip will be lower then --
HipCenter: [200,176,1.908939]
right hip. Spine: [200,167,1.997404]
ShoulderCenter: [203,103,2.132733]
•Spine point will move slightly Head: [203,77,2.194134]
ShoulderLeft: [175,122,2.03505]
up and right. ElbowLeft: [153,165,1.944988]
WristLeft: [146,203,1.788871]
=Movement Up HandLeft: [145,208,1.767767]
ShoulderRight: [228,122,2.061628]
=Movement Down ElbowRight: [245,166,1.962522]
WristRight: [248,204,1.801574]
HandRight: [248,213,1.772346]
HipLeft: [186,188,1.859581]
KneeLeft: [173,260,1.770439]
AnkleLeft: [181,330,1.735953]
FootLeft: [184,348,1.642407]
HipRight: [213,189,1.891124]
KneeRight: [220,260,1.780296]
AnkleRight: [209,333,1.682538]
FootRight: [208,349,1.580602]
Critical Tracking Points (TPs):
1. Head (H)
2. Shoulder_Center (SC)
1. Coding of the slouching metric has been
Associated Tracking Points completed
(TPs): 2. Other definitions shown in this poster are
1. Shoulder_Right (SR) being developed
2. Shoulder_Left (SL) 3. Goal of the model is to work on providing
feedback to the subject during interaction