Journal
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
Volume 119, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.jag.2023.103324
Keywords
Semantic -guided; Building reconstruction; Triangle meshes; Space partition with contour; Structural recovery
Categories
Ask authors/readers for more resources
We propose a semantic-guided building reconstruction method called SGR, which can achieve independent and complete reconstruction of building models. The method consists of two key stages: 2.5D convex cell complex representation for space partition and semantic-guided graph-cut formulation to eliminate interference. Experimental results show that SGR can authentically reconstruct weakly observed surfaces and obtain watertight models considering fidelity, integrity, and time complexity.
Planar primitives tend to be incorrectly detected or incomplete in complex scenes where adhesions exist between different objects, resulting in topology errors in the reconstructed models. We propose a semantic-guided building reconstruction method known as semantic-guided reconstruction (SGR), which is capable of achieving the independence and integrity of building models in two key stages. In the first stage, the space partition is represented by a 2.5D convex cell complex and is capable of restoring planar primitives that are easily lost and can further infer the potential structural adaptivity. The second stage incorporates semantic information into a graph-cut formulation that can assist in the independent reconstruction of buildings while eliminating interference from the surrounding environment. Our experimental results confirmed that the SGR method can authentically reconstruct weakly observed surfaces. Furthermore, qualitative and quantitative evaluations show that SGR is suitable for reconstructing surfaces from insufficient data with semantic and geometric ambiguity or semantic errors and can obtain watertight models considering fidelity, integrity and time complexity.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available