Fusion of color and depth information for image segmentation

The goal of this research is to fuse color and depth information to generate good image segmentation. The image segmentation topic has been studied for several decades. But only recently the use of depth data becomes popular due to the wide spread of affordable and accessible depth cameras such as Microsoft Kinect. The availability of depth information opens up new opportunities for image segmentation. Many methods have developed on color image segmentation over the years. Only recently, several papers are published on image segmentation using both the depth information and the color information. In this research, we focus on how to combine the depth and color information to improve the state of art color image segmentation methods. We adopt a few existing schemes and fuse their outputs to produce the final results. We exploit the planar information to improve the color segmentation. The result is quite satisfactory on both human perception and objective measures.