Human Detection Using Depth Information by Kinect

Abstract

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.