Monocular vision-based depth map extraction method for 2D to 3D video conversion

NCUIR > College of Electrical Engineering & Computer Science > Department of Electrical Engineering > journal & Dissertation > Item 987654321/107813

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107813

Title:	Monocular vision-based depth map extraction method for 2D to 3D video conversion
Authors:	蔡宗漢;Tsai, Tsung-Han;Fan, Chen-Shuo
Contributors:	資訊電機學院電機工程學系
Keywords:	Biometrics;Conversion;Engineering;Extraction;Image Processing and Computer Vision;Motion compensation;Motion simulation;Pattern Recognition;Segmentation;Signal,Image and Speech Processing;Three dimensional;Two dimensional;Visual
Date:	2016-12-01
Issue Date:	2026-04-23 14:26:32 (UTC+8)
Publisher:	Springer Publishing Company;Cham: Springer International Publishing
Abstract:	摘要： Due to the demand of 3D visualization and lack of 3D video content, a method converting the 2D to 3D video plays an important role. In this paper, a low-cost and high efficiency post processing method is presented to enjoy the vivid 3D video. We present two semi-automatic depth map extraction methods for stereo video conversion. For the static background video sequence, we proposed a method which combined the foreground segmentation with vanishing line technology. According to the separated foreground and background results from foreground segmentation algorithm, the viewer can use their acquired visual experience to initiate this operation with some depth information of background. Moreover, we proposed another conversion method for the dynamic background video sequence. Foreground segmentation was replaced by the relative velocity estimation based on the motion estimation and motion compensation. Combining the depth map from this work and the original 2D video, a vivid 3D video is produced. 其他題名： J Image Video Proc 出版者： Cham: Springer International Publishing 出版日期： 2016-06-03 出處： EURASIP journal on image and video processing, 2016-06, Vol.2016 (1), p.1-12, Article 21 資源來源： Springer Nature Link Open Access Journals 版權： Tsai and Fan. 2016 版權： The Author(s) 2016 識別號： ISSN: 1687-5281 識別號： ISSN: 1687-5176 識別號： EISSN: 1687-5281 識別號： DOI: 10.1186/s13640-016-0121-x
Appears in Collections:	[Department of Electrical Engineering] journal & Dissertation

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