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Jim Thomas, Ahsan Kareem and Kevin W. Bowyer,
Automated post-storm damage classification of low-rise building roofing systems using high resolution aerial imagery,
IEEE Transactions on Geoscience and Remote Sensing 52 (7), 3851-3861, July 2014.
link to this paper in IEEE Xplore.
Techniques concerning postdisaster assessment from remotely sensed images have been studied
by different research communities in the past decade. Such an assessment benefits a range of
stakeholders, e.g., government organizations, insurance industry, local communities, and
individual homeowners. This work explores detailed damage assessment on an individual building
basis by utilizing supervised classification. In contrast with previous research efforts in the
field, this work attempts at predicting the type of damages such as missing tiles, collapsed
rooftop, and presence of holes, gaps, or cavities. ...
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Fast, Robust Feature-Based Matching for Automatic Image Registration
in Disaster Response Applications,
Jim Thomas, Ahsan Kareem and Kevin W. Bowyer,
IEEE Interational Geoscience and Remote Sensing Symposium (IGARSS), July 2012.
pdf of this paper.
... In this work, we propose a two-step approach to achieve fast and robust
registration of before- / after-disaster aerial image pairs.
This problem is difficult because there can be substantial change in
the image content between the two images, and the time of day and lighting
typically are different between the two images. ...
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Color Balancing for Change Detection in Multitemporal Images,
Jim Thomas, Kevin W. Bowyer and Ahsan Kareem,
IEEE Workshop on Applications of Computer Vision,
January 2012, Colorado Springs, CO.
pdf of this paper.
narrated ppt on this work.
... In this paper we address color balancing for the purpose of change detection.
... We evaluated the proposed method against other state-of-the-art ones using a
database consisting of aerial image pairs. The test image pairs were taken at
different times, under different lighting conditions, and with different scene
geometries and camera positions. On this database, our proposed approach
outperformed other state-of-the-art algorithms.
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Towards a robust automated hurricane damage assessment from high-resolution images,
James Thomas, Ahsan Kareem, and Kevin W. Bowyer,
13th International Conference on Wind Engineering (ICWE 13), July 2011.
pdf of this paper.
In the event of a natural disaster such as hurricane or earthquake, estimating the extent of
damage is necessary for implementing fast and effective recovery measures. Images of affected
areas are easily obtained through satellite or aerial sensors. The key objects of interest
in such images are buildings, as damage directly impacts lives. This work aims to build a system
capable of fine-grained damage analysis by comparing before and after storm images. ...
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Efficacy of Damage Detection Measures from Aerial Images,
Jim Thomas, Ahsan Kareem and Kevin W. Bowyer,
11-th Americas Conference on Wind Engineering, June 2009.
pdf of this paper.
Estimating the extent of damage caused by natural disasters is necessary for
implementing effective recovery measures. Aerial images of affected areas are
easily obtained through satellite or aerial sensors. A careful analysis of
images from before and after an event facilitates rapid detection and assessment
of damage. Significant previous research has been done on developing measures to
quantify the damage. In this study we evaluate the efficacy of existing change
measures used to estimate damage. Determining the efficacy of these damage measures
in definitive characterization of damage states is necessary for accurate automated
assessment of windstorm damage.
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