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| author | Thibaut Horel <thibaut.horel@gmail.com> | 2012-03-02 03:05:24 -0800 |
|---|---|---|
| committer | Thibaut Horel <thibaut.horel@gmail.com> | 2012-03-02 03:05:24 -0800 |
| commit | 3a61a1866985426ea5593ac56c2696f5caf4ff16 (patch) | |
| tree | 8cfe68996caa3c1bc33a60eba5ed8df8d92d1311 /intro.tex | |
| parent | ee2bb01590dd959cc0c844daceb9d9819a3d5679 (diff) | |
| download | kinect-3a61a1866985426ea5593ac56c2696f5caf4ff16.tar.gz | |
Minor corrections.
Diffstat (limited to 'intro.tex')
| -rw-r--r-- | intro.tex | 26 |
1 files changed, 15 insertions, 11 deletions
@@ -31,15 +31,19 @@ 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. -The paper is organized as follows. First we discuss prior methods of person -identification, in addition to the advances in the technologies pertaining to -skeleton mapping (Section~\ref{sec:related}). Next we use a dataset of actual -skeletal measurements to show that identification by skeleton is feasible, even -when we simulate the error of measuring skeletons with a Kinect -(Section~\ref{sec:}). Finally, we Lastly, we collect skeleton data with a -Kinect in an uncontrolled setting and we apply preprocessing and classification -algorithms to this dataset (Section~\ref{sec:}). We evaluate the performance -of skeleton recognition with varying group size and compare it to face -recognition. We conclude by discussing challenges working with the Kinect and -future work (Section~\ref{sec:conclusion}). +The paper is organized as follows. First we discuss prior methods of +person identification, in addition to the advances in the technologies +pertaining to skeleton mapping (Section~\ref{sec:related}). Next we +use a dataset of actual skeletal measurements to show that +identification by skeleton is feasible, even when we simulate the +error of measuring skeletons with a Kinect +(Section~\ref{sec:uniqueness}). We then discuss an error model and the +resulting algorithm to do person identification +(Section~\ref{sec:algorithm}). Finally, we collect skeleton data with +a Kinect in an uncontrolled setting and we apply preprocessing and +classification algorithms to this dataset +(Section~\ref{sec:experiment}). We evaluate the performance of +skeleton recognition with varying group size and compare it to face +recognition. We conclude by discussing challenges working with the +Kinect and future work (Section~\ref{sec:conclusion}). |
