Real-Time Refinement of Kinect Depth Maps using Multi-Resolution Anisotropic Diffusion

In this paper, we present a novel real-time algorithm to refine depth maps generated by low-cost commercial depth sensors like the Microsoft Kinect. The Kinect sensor falls under the category of RGB-D sensors that can generate a high resolution depth map and color image of a scene. They are relatively inexpensive and are commercially available off-the-shelf. However, owing to their low complexity, there are several artifacts that one encounters in the depth map like holes, mis-alignment between the depth map and color image and lack of sharp object boundaries in the depth map. This is a potential problem in applications that require the color image to be projected in 3-D using the depth map. Such applications depend heavily on the depth map and thus the quality of the depth map is of vital importance. In this paper, a novel multi-resolution anisotropic diffusion based algorithm is presented that accepts a Kinect generated depth map and color image and computes a dense depth map in which the holes have been filled and the edges of the objects are sharpened and aligned with the objects in the color image. The proposed algorithm also ensures that regions in the depth map where the depth is properly This work was supported by the Technology Development Program for Commercializing System Semiconductor funded By the Ministry of Trade, industry & Energy (MOTIE, Korea). (No. 10041126, Title: International Collaborative R&BD Project for System Semiconductor) K. R. Vijayanagar · M. Loghman · J. Kim ( ) Illinois Institute of Technology, 3301 South Dearborn Street, Siegel Hall Suite 103, Chicago, IL 60616, USA e-mail: [email protected] K. R. Vijayanagar e-mail: [email protected] M. Loghman e-mail: [email protected] estimated are not filtered and ensures that the depth values in the final depth map are the same values that existed in the original depth map. Experimental results are provided to demonstrate the improvement in the quality of the depth map and also execution time results are provided to prove that the proposed method can be executed in real-time.