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@@ -16,19 +16,22 @@ attained~\cite{liu01,bio-survey}.
Alternatively, biometrics can be divided into physiological and behavioral
traits. Physiological traits include faces, fingerprints, and irises; speech
and gait are behavioral. Face and gait recognition are the most relevent
-biometrics for this paper as they both are unobtrusive and rely on image
-processing. Gait recognition usually involves determining the outline of a
-person from an image~\cite{bio-survey}, but algorithms similar to gait
-recognition have been developed for range cameras as well~\cite{gomez:hgbu11}.
-Face recognition receives a lot of attention from the research
-community~\cite{face-survey}, also including at least one example incorporating
-a range camera~\cite{gordon91}. Since behavioral traits typically are more
+biometrics for this paper as they both can be collected passively and involve
+image processing. Gait recognition usually involves determining the outline of
+a person from an image to measure gait, but can also be measured from floor
+sensors or wearable sensors~\cite{gait-survey}. Face recognition can be broken
+down into three parts: face detection, feature extraction, and identification;
+these three parts are studied both together and separately~\cite{face-survey}.
+We will compare skeleton recognition to face recognition in this paper for the
+following two reasons. First, behavioral traits typically are more
characteristic as opposed to unique for identification beyond a certain
-scale~\cite{seven-issues}, we will compare the results of skeleton recognition
-to face recognition.
-
+scale~\cite{seven-issues}, and second, face recognition is more widely studied
+and accepted as a means of accurate identification~\cite{face-survey}.
+\paragraph{Skeleton mapping}
-Jain~\etal
+but algorithms similar to gait
+recognition have been developed for range cameras as well~\cite{gomez:hgbu11}.
-\paragraph{Skeleton mapping}
+also including at least one example incorporating
+a range camera~\cite{gordon91}.