contributor author | Zixiang Zhou | |
contributor author | Jie Gong | |
contributor author | Mengyang Guo | |
date accessioned | 2017-05-08T22:31:26Z | |
date available | 2017-05-08T22:31:26Z | |
date copyright | March 2016 | |
date issued | 2016 | |
identifier other | 48360279.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/81999 | |
description abstract | Street-level storm damage photos are an essential type of data used in postdisaster damage assessment. However, the existing approaches only leverage such data in a two-dimensional context. The research reported in this paper leveraged the photos collected during Hurricane Sandy to explore image-based three-dimensional (3D) reconstruction for posthurricane residential building damage assessment. Specifically, two commonly used image reconstruction pipelines are employed to reconstruct several impacted residential buildings to evaluate their performances regarding key measurement needs in posthurricane damage assessment. Damage data recorded by a mobile light detection and ranging (LIDAR) system were used as the ground truth for performance evaluation. The study results suggest that image-based 3D reconstruction can adequately support hurricane damage assessment needs for residential buildings. However, for damage assessment tasks which rely on very accurate estimate (generally | |
publisher | American Society of Civil Engineers | |
title | Image-Based 3D Reconstruction for Posthurricane Residential Building Damage Assessment | |
type | Journal Paper | |
journal volume | 30 | |
journal issue | 2 | |
journal title | Journal of Computing in Civil Engineering | |
identifier doi | 10.1061/(ASCE)CP.1943-5487.0000480 | |
tree | Journal of Computing in Civil Engineering:;2016:;Volume ( 030 ):;issue: 002 | |
contenttype | Fulltext | |