Segmentation of depth image using graph cut
YU Jiang-ming, Jieyu Zhao · 2012
A large number of tasks in computer vision involve finding a target from a background image. It is also known as the foreground/background discrimination problem. Various methods have been developed to solve this problem. [1, 2, 10, 11, 12] Newly developed techniques for general purpose of object abstraction use both color and edge information for segmentation purpose. In this paper, we use graph cut methods on images with depth information from A Kinect camera. Also, we apply the approach with pyramid representation. This greatly reduces the time used with the iterative graph cut methods. We estimate the statistic model on the bottom of the pyramid, while use graph cut on the top of the pyramid. This speeds up the whole segmentation process while keeps a good segmentation quality at the same time. When come across the situation like the object's color resembles that of the background but with different depth, our method can still achieve a good result.