From e2f9ed1370b461402f2c39229eccda6dd1072445 Mon Sep 17 00:00:00 2001 From: Jon Whiteaker Date: Tue, 21 Feb 2012 23:53:21 -0800 Subject: first draft intro --- intro.tex | 31 +++++++++++++++++++++++++++++++ 1 file changed, 31 insertions(+) (limited to 'intro.tex') diff --git a/intro.tex b/intro.tex index 625be66..8f67ccd 100644 --- a/intro.tex +++ b/intro.tex @@ -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. + -- cgit v1.2.3-70-g09d2