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NATURAL USER INTERFACE SENSORS FOR HUMAN BODY MEASUREMENT 
J. Boehm 
University College London, Department of Civil, Environmental and Geomatic Engineering, Gower Street, London 
WCIE 6BT UK 
Commission V, WG V/4 
KEY WORDS: Human Body Measurement, Range Camera, Kinect, NUI 
ABSTRACT: 
The recent push for natural user interfaces (NUI) in the entertainment and gaming industry has ushered in a new era of low cost 
three-dimensional sensors. While the basic idea of using a three-dimensional sensor for human gesture recognition dates some years 
back it is not until recently that such sensors became available on the mass market. The current market leader is PrimeSense who 
provide their technology for the Microsoft Xbox Kinect. Since these sensors are developed to detect and observe human users they 
should be ideally suited to measure the human body. We describe the technology of a line of NUI sensors and assess their 
performance in terms of repeatability and accuracy. We demonstrate the implementation of a prototype scanner integrating several 
NUI sensors to achieve full body coverage. We present the results of the obtained surface model of a human body. 
1. INTRODUCTION 
Human body measurement has an established history of 
measurement systems and applications over the past 30 years. 
Applications are varied and range from medical applications to 
applications in fashion and entertainment. Measurement 
systems are typically purpose-built optical scanners. The optical 
measurement principles employed by existing commercial 
solutions are laser line triangulation, active triangulation using 
white light pattern projection and monocular vision. An 
overview of systems and principles is given by (D'Apuzzo, 
2005). Literature reports prices of commercial scanners ranging 
from $35,000 up to $500,000, which has prevented the 
widespread use of these systems so far. 
Natural User Interfaces (NUI) have been promoted for some 
years as the natural successor and addition to Touch User 
Interfaces (TUI) and Graphical User Interfaces (GUI). The idea 
is to free the user from having to hold an input device such as a 
mouse or a stylus or interact on a predefined surface such as a 
touch screen. Instead the user’s natural gestures such as waving 
and pointing are to be recognised and interpreted as input. 
Different sensor systems from monocular cameras to time-of- 
flight cameras have been suggested to capture a user’s gestures. 
However it was not until Microsoft’s introduction of the Kinect 
as a NUI controller to their video game console Xbox 360 that a 
NUI sensor became widely available at a consumer price. The 
impact on the market was immediate. One million Kinect 
sensors were sold in just 10 days after the launch (Microsoft 
Corp., 2010). Adding to these numbers more than 10 million 
units were sold within the first 5 month. 
This easily makes it the 3D sensor with the highest number of 
units sold at probably the lowest price, which has dropped 
below $99 by the time of writing. While originally intended 
only for the use with Microsoft’s video game console, the 
sensor soon attracted applications beyond gaming. However, 
since the sensor is tuned to recognize the human body and its 
pose, applications to measure the human body are the most 
evident. 
  
Within this paper we will demonstrate the application of a NUI 
sensor to human body measurement. We will describe the 
sensor characteristic beyond its specifications given by the 
manufacturer. In order to determine its fit for purpose we also 
report on our tests of the sensor’s repeatability and accuracy. 
While tests of Kinect-like sensors have been performed before, 
we add to these in that we test not only single units but a whole 
set of units to show variations due to production tolerances. We 
report on our prototype implementation of an 8 sensor set-up 
and show first data sets captured with the system. 
2. RELATED WORK 
Weiss et al. (2011) have proposed a single sensor body scanner 
for home use based on the Microsoft Kinect. In order to capture 
the full body the user has to move into different poses in front 
of the fixed sensor. When users are moving into different poses 
their body shapes are obviously changing. Approaches based on 
the single fixed sensor principle thus have to accommodate for 
the changes in shape. The authors use a body model named 
SCAPE which considers 3D body shape and pose variations. 
The full 3D model thus is not a direct result of sensor readings 
but a combination of sensor readings and an underlying body 
model. 
Newcombe and Davison (2010) have developed a structure 
from motion (SFM) approach to integrate depth maps from a 
moving Kinect sensor. The system has been further developed 
into the KinectFusion system (Newcombe et al., 2011). A single 
sensor is slowly moved around an object or a scene to fully 
capture it. The main contribution is the real-time capability of 
the system, which allows a user to interactively build (capture) 
a full scene. The downside to capturing whole body models is 
that due to the nature of the SFM approach, displacements 
between frames should be small to allow for optimal alignment. 
Thus motion is slow and it takes some time to capture a full 
body model during which the captured human may not move. 
Other notable contributions of this work include the innovative 
representation of the scene as volumetric elements and the 
introduction of bilateral filtering to depth maps from a NUI 
Sensor.