Method for enhancing low quality depth maps for 3D reconstruction on a embedded platform

In the recent past, vast amounts of stereo and augmented reality based applications are being developed for hand-held devices. In most of these applications depth map is a key ingredient for acceptable user experience. Accuracy and high density of depth map are important along with meeting real-time constraints on an embedded system. There is an inherent tradeoff between depth map quality and speed and invariably performance is usually important for competing in todays high-definition video marketplace. In this paper we present a method that addresses depth map quality while still maintaining performance at video frame-rates. Specifically, we discuss a technique to enhance a low-quality depth map for 3D point cloud generation on an embedded platform. We provide performance metrics and estimates on a Texas Instruments (TI) OMAP embedded platform and show that using simple pre and post-processing techniques one can achieve both quality and performance. A preliminary version of our point cloud application developed has a frame rate of about 15fps, majority being display and rendering related overheads. The core algorithms including pre and post processing have a much higher frame rate of about 23-25fps. We estimate that with adequate mapping of the algorithms to various cores and accelerated kernels, the frame rate could reach real-time performance of 30fps.