NDLI: MSCS: MeshStereo with Cross-Scale Cost Filtering for fast stereo matching

Content Provider	IET Digital Library
Author	Yao, Peng Zhang, Hua Xue, Yanbing Chen, Shengyong
Abstract	MeshStereo (MS) and cross-scale cost filtering (CSCF) are two most recently celebrated models for stereo matching. On one hand, MS model enlightens for fast solving the dense stereo correspondence problem according to a region-based opinion. On the other hand, CSCF model could generate more robust matching cost volumes than single scale. In this study, the authors weave these two models together for attaining greater and faster disparity estimation. With CSCF, more powerful initial volumes of matching cost are computed and they are conducted as the data term of MS energy function model. More importantly, the novel-fused stereo model also draws a closer connection between multi-scale aggregated and global algorithms. Integrating the advantages of both stereo models, they name the presented one as MS with cross-scale (MSCS). Performance evaluations on Middlebury v.2 and v.3 stereo data sets demonstrate that the proposed MSCS outperforms other four most challenging stereo matching algorithms; and also performs better on Microsoft i2i stereo videos. In addition, thanks to this novel-fused model, MSCS requires fewer iteration times for optimising and makes it surprisingly possesses a much faster execution time.
Starting Page	908
Ending Page	918
Page Count	11
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 6, Sep (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2017.0599
Journal	IET Computer Vision
Publisher Date	2018-04-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique CSCF Model Data Term Dense Stereo Correspondence Problem Disparity Estimation Fast Stereo Matching Filtering Method in Signal Processing Global Algorithm Image Filtering Image Matching Image Recognition Matching Cost MeshStereo Microsoft I2i Stereo Videos Middlebury V.2 Stereo Data Sets Middlebury V.3 Stereo Data Sets MS Energy Function Model MS with Cross-scale Cost Filtering MSCS Multiscale Aggregated Algorithm Novel-fused Stereo Model Region-based Opinion Robust Matching Cost Volumes Stereo Image Processing Video Signal Processing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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