Conventional human detection is mostly done in images
taken by visible-light cameras. These methods imitate the
detection process that human use. They use features based
on gradients, such as histograms of oriented gradients
(HOG), or extract interest points in the image, such as
scale-invariant feature transform (SIFT), etc. In this paper,
we present a novel human detection method using depth
information taken by the Kinect for Xbox 360. We propose
a model based approach, which detects humans using a
2-D head contour model and a 3-D head surface model. We
propose a segmentation scheme to segment the human from
his/her surroundings and extract the whole contours of the
figure based on our detection point. We also explore the
tracking algorithm based on our detection result. The
methods are tested on our database taken by the Kinect in
our lab and present superior results.