From f69c178b85958ef0773a97e5946cce722639415e Mon Sep 17 00:00:00 2001 From: Jon Whiteaker Date: Mon, 5 Mar 2012 13:47:41 -0800 Subject: last changes --- conclusion.tex | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) (limited to 'conclusion.tex') diff --git a/conclusion.tex b/conclusion.tex index 40eac53..d423e29 100644 --- a/conclusion.tex +++ b/conclusion.tex @@ -1,15 +1,15 @@ \section{Conclusion} \label{sec:conclusion} -In this paper, we present exciting and promising results for face recognition. -With greater than 90\% accuracy for less than 10 people, skeleton recognition -can already be used in households, \eg to load personalized settings on a home -entertainment system. Skeleton recognition performs less than 10\% worse than -face recognition in the current setting. This is a good result considering -face recognition has been studied for years and is more mature. Furthermore, -skeleton recognition works in many situations when face recognition does not. -For example, when a person is not facing the camera or when there is not enough -light. +In this paper, we present exciting and promising results for skeleton +recognition. With greater than 90\% accuracy for less than 10 people, skeleton +recognition can already be used in households, \eg to load personalized +settings for a home entertainment system. Skeleton recognition performs less +than 10\% worse than face recognition in the current setting. This is a good +result considering face recognition has been studied for years and is more +mature. Furthermore, skeleton recognition works in many situations when face +recognition does not. For example, when a person is not facing the camera or +when it is dark. %we introduce skeleton recognition. We show that skeleton %measurements are unique enough to distinguish individuals using a dataset of -- cgit v1.2.3-70-g09d2