NDLI: The image depth estimation based on multi-scale texture features and least-square method

Content Provider	IEEE Xplore Digital Library
Author	Zhang, Lizhi Chen, Tingting Sun, Huadong Zhao, Zhijie Jin, Xuesong Huang, Ju
Copyright Year	2014
Description	Author affiliation: School of Computer and Information Engineering, Harbin University of Commerce, 150028, China (Zhang, Lizhi; Chen, Tingting; Sun, Huadong; Zhao, Zhijie; Jin, Xuesong; Huang, Ju)
Abstract	The technique of 3D scene reconstruction from 2D scene image can satisfy the demands of 3D display market, and it is the main research contents in the field of image processing. For the 3D reconstruction, the extraction of depth cues is one of the most important contents. Therefore, we proposed a least-square depth estimation method based on multi-scale texture features, which can better describe the relationship between the texture characteristics and the scene depth. first we captured the texture energy of different scales as the features of the image using Laws' filters to image texture gradients, texture variations and colors, respectively, and then we trained these features of the training sample sets to get the relationship parameters between texture cues and scene depth, which can finally be applied to estimate the depth of the test sample sets. The experimental results show that the method we proposed performs well in scene depth information extraction, meanwhile it requires less constraint for scene structure and space layout of 2D images. Consequently, it has good robustness because it need no specific analysis to the images with special depth cues such as linear perspective.
Starting Page	816
Ending Page	820
File Size	791880
Page Count	5
File Format	PDF
ISBN	9781479921881
ISSN	21645221
e-ISBN	9781479921867
DOI	10.1109/ICOSP.2014.7015117
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-10-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Training Estimation Filtering theory Pattern recognition Feature extraction Image texture texture feature Multi-scale texture least-square depth estimation
Content Type	Text
Resource Type	Article

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