Depth Image Processing

Abstract

The production of three-dimensional data is the primary function of Kinect. It is up to you to create exciting experiences with the data. A precondition to building a Kinect application is having an understanding of the output of the hardware. Beyond simply understanding, the intrinsic meaning of the 1’s and 0’s is a comprehension of its existential significance. Image-processing techniques exist today that detect the shapes and contours of objects within an image. The Kinect SDK uses image processing to track user movements in the skeleton tracking engine. Depth image processing can also detect non-human objects such as a chair or coffee cup. There are numerous commercial labs and universities actively studying techniques to perform this level of object detection from depth images. There are many different uses and fields of study around depth input that it would be impossible to cover them or cover any one topic with considerable profundity in this book much less a single chapter. The goal of this chapter is to detail the depth data down to the meaning of each bit, and introduce you to the possible impact that adding just one additional dimension can have on an application. In this chapter, we discuss some basic concepts of depth image processing, and simple techniques for using this data in your applications.