Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/58084
Title: Local, global and segment-based stereo matching
Authors: Shahzor Ahmad
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Issue Date: 2011
Abstract: Stereo matching involves the estimation of depth from two or more images of the same scene taken from different view-points. It finds applications in areas such as dense 3D reconstruction of scenes and object models, depth image based rendering, autonomous robot navigation, satellite imaging and automated cartography. This dissertation explores three classes of algorithms for stereo matching, the first step in recovering depth from stereo. The three classes are local, global and segment-based algorithms, each one outperforming the ones preceding it. The main theme of local matching techniques is presented, an implementation is described and a constraint to keep a check on false matches is illustrated. The basic concepts of global energy minimization in computer vision are presented before describing three global optimization algorithms in the context of stereo matching - graph-cuts, belief propagation and dynamic programming. A general structure of the segment-based approaches is developed and the related work is reviewed. A complete software implementation is developed and some of the issues involved are discussed. 3D point-cloud plots from practical experiments are used to illustrate the main steps of segment-based techniques. For each class of algorithms, experimental results are presented and their qualitative and quantitative evaluation is performed.
Description: 86 p.
URI: http://hdl.handle.net/10356/58084
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
EEE THESES_22.pdf
  Restricted Access
11.8 MBAdobe PDFView/Open

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.