Stereoview to Multiview Conversion Architecture for Auto-Stereoscopic 3D Displays

Pin Chen Kuo; Kuan Lun Lo; Huan Kai Tseng; Kuan Ting Lee; Bin Da Liu; Jar Ferr Yang

doi:10.1109/TCSVT.2017.2732061

Stereoview to Multiview Conversion Architecture for Auto-Stereoscopic 3D Displays

Pin Chen Kuo, Kuan Lun Lo, Huan Kai Tseng, Kuan Ting Lee, Bin Da Liu, Jar Ferr Yang

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

In this paper, a stereoview to multiview conversion system, which includes stereo matching and depth image-based rendering (DIBR) hardware designs, is proposed. To achieve an efficient architecture, the proposed stereo matching algorithm simply generates the raw matching costs and aggregates cost based on 1D iterative aggregation schemes. For the DIBR architecture, an inpainting-based method is used to find the most similar patch from the background, according to depth information. The simulation results show that the designed architecture achieves an averaged peak signal-to-noise ratio of 30.2 dB and structure similarity of 0.94 for the tested images. The hardware design for the proposed 2D to 3D conversion system operates at a maximum clock frequency of 160.2 MHz for outputting 1080p (1920 × 1080) video at 60 frames per second.

Original language	English
Article number	7993031
Pages (from-to)	3274-3287
Number of pages	14
Journal	IEEE Transactions on Circuits and Systems for Video Technology
Volume	28
Issue number	11
DOIs	https://doi.org/10.1109/TCSVT.2017.2732061
Publication status	Published - 2018 Nov

All Science Journal Classification (ASJC) codes

Media Technology
Electrical and Electronic Engineering

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10.1109/TCSVT.2017.2732061

Cite this

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title = "Stereoview to Multiview Conversion Architecture for Auto-Stereoscopic 3D Displays",

abstract = "In this paper, a stereoview to multiview conversion system, which includes stereo matching and depth image-based rendering (DIBR) hardware designs, is proposed. To achieve an efficient architecture, the proposed stereo matching algorithm simply generates the raw matching costs and aggregates cost based on 1D iterative aggregation schemes. For the DIBR architecture, an inpainting-based method is used to find the most similar patch from the background, according to depth information. The simulation results show that the designed architecture achieves an averaged peak signal-to-noise ratio of 30.2 dB and structure similarity of 0.94 for the tested images. The hardware design for the proposed 2D to 3D conversion system operates at a maximum clock frequency of 160.2 MHz for outputting 1080p (1920 × 1080) video at 60 frames per second.",

author = "Kuo, {Pin Chen} and Lo, {Kuan Lun} and Tseng, {Huan Kai} and Lee, {Kuan Ting} and Liu, {Bin Da} and Yang, {Jar Ferr}",

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AU - Tseng, Huan Kai

AU - Lee, Kuan Ting

AU - Liu, Bin Da

AU - Yang, Jar Ferr

PY - 2018/11

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Stereoview to Multiview Conversion Architecture for Auto-Stereoscopic 3D Displays

Abstract

All Science Journal Classification (ASJC) codes

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