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A Local Adaptive Approach for Dense Stereo Matching in Architectural Scene Reconstruction : Volume Xl-5/W1, Issue 1 (13/02/2013)

By Stentoumis, C.

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Book Id: WPLBN0004015293
Format Type: PDF Article :
File Size: Pages 8
Reproduction Date: 2015

Title: A Local Adaptive Approach for Dense Stereo Matching in Architectural Scene Reconstruction : Volume Xl-5/W1, Issue 1 (13/02/2013)  
Author: Stentoumis, C.
Volume: Vol. XL-5/W1, Issue 1
Language: English
Subject: Science, Isprs, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus Publications
Historic
Publication Date:
2013
Publisher: Copernicus Publications, Göttingen, Germany
Member Page: Copernicus Publications

Citation

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Grammatikopoulos, L., Petsa, E., Kalisperakis, I., Stentoumis, C., & Karras, G. (2013). A Local Adaptive Approach for Dense Stereo Matching in Architectural Scene Reconstruction : Volume Xl-5/W1, Issue 1 (13/02/2013). Retrieved from http://community.worldlibrary.net/


Description
Description: Laboratory of Photogrammetry, Department of Surveying, National Technical University of Athens, 15780 Athens, Greece. In recent years, a demand for 3D models of various scales and precisions has been growing for a wide range of applications; among them, cultural heritage recording is a particularly important and challenging field. We outline an automatic 3D reconstruction pipeline, mainly focusing on dense stereo-matching which relies on a hierarchical, local optimization scheme. Our matching framework consists of a combination of robust cost measures, extracted via an intuitive cost aggregation support area and set within a coarse-tofine strategy. The cost function is formulated by combining three individual costs: a cost computed on an extended census transformation of the images; the absolute difference cost, taking into account information from colour channels; and a cost based on the principal image derivatives. An efficient adaptive method of aggregating matching cost for each pixel is then applied, relying on linearly expanded cross skeleton support regions. Aggregated cost is smoothed via a 3D Gaussian function. Finally, a simple winnertakes- all approach extracts the disparity value with minimum cost. This keeps algorithmic complexity and system computational requirements acceptably low for high resolution images (or real-time applications), when compared to complex matching functions of global formulations. The stereo algorithm adopts a hierarchical scheme to accommodate high-resolution images and complex scenes. In a last step, a robust post-processing work-flow is applied to enhance the disparity map and, consequently, the geometric quality of the reconstructed scene. Successful results from our implementation, which combines pre-existing algorithms and novel considerations, are presented and evaluated on the Middlebury platform.

Summary
A LOCAL ADAPTIVE APPROACH FOR DENSE STEREO MATCHING IN ARCHITECTURAL SCENE RECONSTRUCTION

 

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