diff options
| -rw-r--r-- | intro.tex | 31 | ||||
| -rw-r--r-- | kinect.bib | 220 | ||||
| -rw-r--r-- | kinect.tex | 19 |
3 files changed, 32 insertions, 238 deletions
@@ -1,2 +1,33 @@ \section{Introduction} \label{sec:intro} + +Person identification has become a valuable asset, whether for means of +authentication, personalization, or other applications. Previous work revolves +around either physiological biometrics, such as face recognition, or behavioral +biometrics such as voice or gait recognition. In this paper, we propose using +skeletal measurements as a new physiological biometric for recognition. + +In recent years, advances in range cameras have given us access to increasingly +accurate real-time depth imaging. Furthermore, the low-cost and widely +available Kinect~\cite{kinect} has brought range imaging to the masses. In +parallel, the automatic detection of body parts from depth images has led to +real-time skeleton mapping. As the resolution and accuracy of range cameras +improve, so will the accuracy and precision of skeleton mapping algorithms. + +In this paper we show that skeleton mapping is accurate and unique enough in +individuals to be used for person recognition. First, we show that ground +truth skeleton measurements can uniquely identify a person. Second, we show +how the accuracy of skeleton recognition decreases as simulated error +increases. Third, we collect skeleton data with a Kinect in an uncontrolled +setting and we apply preprocessing and classification algorithms to this +dataset. We evaluate the performance of skeleton recognition with varying +group size and compare it to face recognition. + +Much of the prior work in person recognition focuses on data gathered from +other sensors, such as face recognition with color cameras and voice +recognition with microphones. In the realm of depth imaging, most of the work +surrounds behavioral recognition, continuing work in gait recognition. The +Xbox 360~\cite{} does use the height inferred from the Kinect as part of its +user identification algorithm, albeit in addition to other attributes including +face recognition. + diff --git a/kinect.bib b/kinect.bib deleted file mode 100644 index a3042f0..0000000 --- a/kinect.bib +++ /dev/null @@ -1,220 +0,0 @@ -
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@@ -47,23 +47,6 @@ \maketitle -%\title{Twenty Questions} -% -%\author{ -% \hspace{-1em} -% \begin{minipage}{\textwidth} -% \setlength{\aulen}{0.24\linewidth} -% \centering -% \auboxs{\aulen}{Jon Whiteaker\fnsym{tc}} -% \auboxs{\aulen}{Branislav Kveton\fnsym{tc}} -% \\[0.5\baselineskip] -% \affaddr -% \setlength{\aulen}{0.49\linewidth} -% \affbox{\aulen}{\fnsym{tc}Technicolor}{<firstname>.<lastname>@technicolor.com} -% \end{minipage} -%} -% -%\maketitle % Use the following at camera-ready time to suppress page numbers. % Comment it out when you first submit the paper for review. @@ -80,7 +63,7 @@ { \bibliographystyle{splncs} -\bibliography{kinect} +\bibliography{references} } %Features\endnote{Remember to use endnotes, not footnotes!} galore, plethora of promises.\\ |