PhD Thesis - Automated Recognition of 3D CAD Model Objects in ...

Introduction 4
1.5 Structure of the Thesis
This thesis presents the results of the research that has been conducted toward
achieving these objectives.
Chapter 2 first presents the context of construction project management objectives
and their relationship to emerging automated data acquisition paradigms.
Performance metrics and objectives are established for 3D object recognition systems
within this context. 3D range imaging technologies and their potential impact
on industry practices are presented. The limitations of current systems for 3D image
processing in the AEC&FM industry lead to the review of existing approaches
for automated 3D object recognition. 3D CAD modeling and registration technologies
available to the AEC&FM industry are then introduced resulting in the
reformulation of the classic 3D object recognition problem in this specific context.
The expected performance of existing automated 3D object recognition solutions
to this new problem is finally reviewed.
Chapter 3 presents a novel approach for 3D object recognition in 3D images
that is developed specifically for taking better advantage of the 3D modeling and
registration technologies available in the AEC&FM industry context.
Chapter 4 presents experimental results demonstrating the performance of the
proposed approach in terms of accuracy, efficiency, robustness and level of automation.
Finally, Chapter 5 presents experimental results that demonstrate how the developed
approach can be used to automatically construct a P4dIM enabling multiple
APPC applications, in particular automated construction 3D progress control
and automated dimensional QA/QC. Two other interesting applications are also
presented including: planning for scanning and strategic scanning.
Chapter 6 summarizes the contribution of this research. The limitations of the
developed approach and of its use for constructing of P4dIMs are reviewed, and
areas of future research suggested.