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PhD Dissertation Defense - Matt O’Banion

Rigorous 3D Point Cloud Quality Assessment

Thursday, October 12, 2017 10:00 AM - 12:00 PM

Student: Matt O’Banion

Advisor: Michael J. Olsen


The capabilities of modern three-dimensional (3D) capture technology such as laser scanning and image-based 3D reconstruction are well suited for enhancing the practice and research of civil engineering. However, given the often-overwhelming focus placed on the incredible capabilities of these tools and techniques, it is important to investigate the limitations of these technologies to ensure they are not misused. Currently, limited resources are available to assist in the evaluation of geospatial 3D point cloud data quality, which makes it difficult to efficiently quantify, and communicate the limitations of such data.

This research investigates the occurrence of data gaps in terrestrial laser scanning (TLS)-derived digital elevation models (DEMs), the quality and accuracy of Structure from Motion (SfM) image-based 3D reconstructions, and the inherent positional uncertainty of individual points in a TLS point cloud. Novel approaches for the detection and classification of data gaps, the evaluation of data suitability, and the efficient computation and visualization of per-point TLS point cloud uncertainty will be discussed. 


Kearney Hall (campus map)
311
Michelle McAllaster
michelle.mcallaster at oregonstate.edu
Sch of Civil/Constr Engr
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