Real-Time 3D Depth Generation for Stereoscopic Video Applications with Thread-Level Superscalar-Pipeline Parallelization

We propose a low-complexity algorithm for stereoscopic video applications that generates a high-quality 3D image depth map from a single 2D image. Based on their characteristics, 2D images are classified into one of three categories before being processed by the proposed lowcomplexity algorithm to generate corresponding depth maps. We also extend the 3D depth algorithm to construct a parallel 3D video system. A thread-level superscalarpipelining approach is developed to parallelize the 3D video system. Experimental results for HD1080 resolution images demonstrate that the algorithm can generate high-quality depth maps with an average reduction in the computational complexity of 98.2 % compared with a conventional algorithm. The parallel 3D video system can achieve a processing speed of 63.66 fps for HD720 resolution video.