View planning for range acquisition of indoor environments Public Deposited

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  • March 22, 2019
  • Low, Kok-Lim
    • Affiliation: College of Arts and Sciences, Department of Computer Science
  • This dissertation presents a new and efficient next-best-view algorithm for 3D reconstruction of indoor environments using active range sensing. A major challenge in range acquisition for 3D reconstruction is an efficient automated view planning algorithm to determine a sequence of scanning locations or views such that a set of acquisition constraints and requirements is satisfied and the object or environment of interest can be satisfactorily reconstructed. Due to the intractability of the view planning problem and the lack of global geometric information, a greedy approach is adopted to approximate the solution. A practical view metric is formulated to include many real-world acquisition constraints and reconstruction quality requirements. This view metric is flexible to allow trade-offs between different requirements of the reconstruction quality. A major contribution of this work is the application of a hierarchical approach to greatly accelerate the evaluation of the view metric for a large set of views. This is achieved by exploiting the various spatial coherences in the acquisition constraints and reconstruction quality requirements when evaluating the view metric. The hierarchical view evaluation algorithm is implemented in a view planning system targeted for the acquisition of indoor environments using a monostatic range scanner with 3D pose. The results show great speedups over the straightforward method used in many previous algorithms. The view planning system has also been shown to be robust for real-world application. The dissertation also describes how the view metric can be generalized to incorporate general acquisition constraints and requirements, and how the hierarchical view evaluation algorithm can be generalized to scanners with general pose, and to scanners with bistatic sensors. A simple extension is also proposed to enable the hierarchical view evaluation algorithm to take into account each view's sensitivity to the potential pose errors in the physical positioning of the scanner. A computed new view must produce a range image that can be accurately registered to the previous scans. In this work, a metric is developed to estimate the registration accuracy of the views. This metric considers the amount of overlap, the range measurement errors, and the shape complexity of the surfaces.
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  • In Copyright
  • Lastra, Anselmo
Degree granting institution
  • University of North Carolina at Chapel Hill
  • Open access

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