summaryrefslogtreecommitdiffstats
path: root/related.tex
diff options
context:
space:
mode:
authorJon Whiteaker <jbw@berkeley.edu>2013-03-20 23:29:41 -0700
committerJon Whiteaker <jbw@berkeley.edu>2013-03-20 23:29:41 -0700
commit2ec78535e079c799c03635b834bdfeafe0b4f6e6 (patch)
treea5d6acfae72d8e8810bfc1c1b3d2d846eb66afa4 /related.tex
parent01ebb22aeeb55d221d49c023df37534764a93b92 (diff)
downloadkinect-2ec78535e079c799c03635b834bdfeafe0b4f6e6.tar.gz
did a pass on the paper, made some minor changes and did some cutting to get it under 8 pages
Diffstat (limited to 'related.tex')
-rw-r--r--related.tex22
1 files changed, 13 insertions, 9 deletions
diff --git a/related.tex b/related.tex
index 1ac25d9..561c041 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 fall into two categories: silhouette-based and
+Approaches to gait recognition typicaly 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
@@ -56,17 +56,21 @@ 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
-capture~\cite{mocap-survey}. Specifically, range cameras offer real-time depth
-imaging, and the Kinect~\cite{kinect} in particular is a widely available range
-camera with a low price point. Figure detection and skeleton fitting have also
-been studied in motion capture, mapping to region of interest detectors and
-human body part identification or pose estimation respectively in this
+capture~\cite{mocap-survey}.
+%Specifically, range cameras offer real-time depth
+%imaging, and
+The Kinect~\cite{kinect} is a widely available 3-D sensor (also known as a
+range camera) with a low price point, that has been leveraged to improve gait
+recognition~\cite{munsell:eccv12,hoffman:btas12}. Figure detection and
+skeleton fitting have also been studied in motion capture, mapping to region of
+interest detectors and human body part identification or pose estimation
+respectively in this
context~\cite{plagemann:icra10,ganapathi:cvpr10,shotton:cvpr11}. Furthermore,
OpenNI~\cite{openni} and the Kinect for Windows SDK~\cite{kinect-sdk} are two
systems that perform figure detection and skeleton fitting for the Kinect.
-Given the maturity of the solutions, we will use existing implementations of figure
-detection and skeleton fitting. Therefore this paper will focus primarily on
-the classification part of skeleton recognition.
+Given the maturity of the solutions, we will use existing implementations of
+figure detection and skeleton fitting. Therefore this paper will focus
+primarily on the classification part of skeleton recognition.
%a person from an image to measure gait, but can also be measured from floor