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| author | Thibaut Horel <thibaut.horel@gmail.com> | 2013-03-30 18:53:00 +0100 |
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| committer | Thibaut Horel <thibaut.horel@gmail.com> | 2013-03-30 18:53:00 +0100 |
| commit | 963c5190b75f5bc2e7557a2da13a400cf1f17461 (patch) | |
| tree | 1acc4e23a057e4cf4cf5ea54a16eadde8b370fb2 /related.tex | |
| parent | c32124428d70eb4a56336ba250d5ff4be93f1751 (diff) | |
| download | kinect-963c5190b75f5bc2e7557a2da13a400cf1f17461.tar.gz | |
Typo fixes
Diffstat (limited to 'related.tex')
| -rw-r--r-- | related.tex | 4 |
1 files changed, 2 insertions, 2 deletions
diff --git a/related.tex b/related.tex index ff5a763..a575c97 100644 --- a/related.tex +++ b/related.tex @@ -19,7 +19,7 @@ Physiological traits include faces, fingerprints, and irises; speech and gait are behavioral. Faces and gait are the most relevant biometrics for this paper as they both can be collected passively and involve image processing. -Approaches to gait recognition typicaly fall into two categories: silhouette-based and +Approaches to gait recognition typically fall into two categories: silhouette-based and model-based. Silhouette-based techniques recognize gaits from a binary representation of the silhouette as extracted from each image, while model-based techniques fit a 3-D model to the silhouette to better track @@ -55,7 +55,7 @@ model fitting in gait detection, but as previously noted, they are severely limited. However, Zhao~\etal~\cite{zhao20063d} perform gait recognition in 3-D using multiple cameras. By moving to 3-D, many of the problems related to silhouette extraction and model fitting are removed. Additionally we can take -advantage of the wealth of research relating to 3-D motion +advantage of the wealth of research relating to \mbox{3-D} motion capture~\cite{mocap-survey}. %Specifically, range cameras offer real-time depth %imaging, and |