diff options
| author | Jon Whiteaker <jbw@berkeley.edu> | 2012-03-05 11:12:04 -0800 |
|---|---|---|
| committer | Jon Whiteaker <jbw@berkeley.edu> | 2012-03-05 11:12:04 -0800 |
| commit | 73834f5ef1c7be73d054baf4cf5f14a39fef17dc (patch) | |
| tree | 81e50a05b90a8ad2e7b9eb781c32a44d8fe9146f /abstract.tex | |
| parent | 19bb0ff0935f8adc4b63ffd8e8aa58706bdcf7a2 (diff) | |
| download | kinect-73834f5ef1c7be73d054baf4cf5f14a39fef17dc.tar.gz | |
jon's final pass part one
Diffstat (limited to 'abstract.tex')
| -rw-r--r-- | abstract.tex | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/abstract.tex b/abstract.tex index 9386d11..4940b90 100644 --- a/abstract.tex +++ b/abstract.tex @@ -1,11 +1,11 @@ \begin{abstract} - This paper explores a novel approach for person recognition based on - skeletal measurements. After showing that exact measurements allow - for accurate recognition, we study two algorithmic approaches for - identification in case of approximate measurements. A real-life - experiment with 25 people and measurements obtained from the Kinect - range camera gives us promising results and comparison with state of - the art facial recognition validates the viability of - skeleton-based identification. -\end{abstract} + This paper explores a novel approach for person recognition based on skeletal + measurements. After showing that exact measurements allow for accurate + recognition in a large dataset, we study two algorithmic approaches for + recognition given approximate measurements. We perform a real-world + experiment with measurements captured from the Kinect and obtain 95\% + accuracy with three people and 85\% accuracy with five people. Our results + and a comparison with state of the art facial recognition validate the + viability of skeleton-based recognition. + \end{abstract} |
