diff options
| author | Jon Whiteaker <jbw@berkeley.edu> | 2012-02-28 11:38:13 -0800 |
|---|---|---|
| committer | Jon Whiteaker <jbw@berkeley.edu> | 2012-02-28 11:44:24 -0800 |
| commit | fe82056dd532b070442edab1e43797729c38f9fd (patch) | |
| tree | 4991aecaf19294615999672c3638f7f42e21f416 | |
| parent | b072ca61a5bf1b36fb6eaa06232bfc5472db4dbf (diff) | |
| download | kinect-fe82056dd532b070442edab1e43797729c38f9fd.tar.gz | |
related work edits
| -rw-r--r-- | related.tex | 27 |
1 files changed, 15 insertions, 12 deletions
diff --git a/related.tex b/related.tex index 98f4a77..02b87a2 100644 --- a/related.tex +++ b/related.tex @@ -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}. |