DocumentCode :
1797352
Title :
A 2D to 3D conversion method based on support vector machine and image classification
Author :
Yu-Dong Guan ; Bo-Liang Yu ; Chun-Li Ti ; Yan Ding
Author_Institution :
Sch. of Electron. & Inf. Eng., Harbin Inst. of Technol., Harbin, China
Volume :
1
fYear :
2014
fDate :
13-16 July 2014
Firstpage :
88
Lastpage :
93
Abstract :
With the development of 3D technology, converting 2D videos available into 3D videos has been an important way to gain 3D contents. In the conversion, a crucial step is how to obtain a more accurate depth map. This paper proposes a method for depth extraction based on color and geometric information of the original image. Firstly, we generate a qualitative depth map by SVM and classify image scenes into three categories. Then depending on geometric information, a geometric depth map can be generated by vanishing lines detection and gradient plane assignment. At last, we blend two depth maps to get a final depth map, which has more widely application and improves accuracy of depth better.
Keywords :
edge detection; gradient methods; image classification; image colour analysis; support vector machines; video signal processing; 2D to 3D conversion method; 2D videos; 3D technology; 3D videos; SVM; color information; depth extraction; geometric depth map; geometric information; gradient plane assignment; image classification; image scene classifcation; qualitative depth map; support vector machine; vanishing lines detection; Abstracts; Image classification; Support vector machines; 2D to 3D; Depth map; Image classification; SVM; Vanishing point detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2014 International Conference on
Conference_Location :
Lanzhou
ISSN :
2160-133X
Print_ISBN :
978-1-4799-4216-9
Type :
conf
DOI :
10.1109/ICMLC.2014.7009097
Filename :
7009097
Link To Document :
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