Abstract

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

Citations