Real-time 3D depth generation for stereoscopic video applications with thread-level superscalar-pipeline parallelization

Guo An Jian, Cheng An Chien, Peng Sheng Chen*, Jiun-In Guo

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

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 low-complexity algorithm to generate corresponding depth maps. We also extend the 3D depth algorithm to construct a parallel 3D video system. A thread-level superscalar-pipelining 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.

Original languageEnglish
Pages (from-to)17-33
Number of pages17
JournalJournal of Signal Processing Systems
Volume72
Issue number1
DOIs
StatePublished - 1 Jul 2013

Keywords

  • 3D image/video
  • Depth map
  • Parallel computing
  • Stereo

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