Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data
By Xuehan Xiong, Antonio Adán, Burcu Akinci, Daniel F. Huber. 2011
744 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Environmental Engineering, Geology
View Paper: https://www.semanticscholar.org/paper/03ac6d231abee7c967733f21e3276e4da42654e9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Silvio Savarese
- Amir Zamir
- Jitendra Malik
- Iro Armeni
- Ozan Sener
- Charles Ruizhongtai Qi
- Saurabh Gupta
- Hengshuang Zhao
In Environmental Engineering
- Silvio Savarese
- Amir Zamir
- Billie F. Spencer Jr.
- Vedhus Hoskere
- Yasutaka Narazaki
- Jitendra Malik
- Charles Ruizhongtai Qi
- Saurabh Gupta
In Geology
- Silvio Savarese
- Amir Zamir
- Iro Armeni
- Jitendra Malik
- Charles Ruizhongtai Qi
- Saurabh Gupta
- Matthias Nießner
- Hengshuang Zhao
Citations in the corpus
- Advances in Computer Vision-Based Civil Infrastructure Inspection and Monitoring (2019, methodology): “Xiong et al. [154] investigated an automated method for converting dense 3D point-cloud data from a room to a semantically rich 3D model represented by planar walls, floors, ceilings, and rectangular openings (a process referred to as Scan-to-Building Information Modeling (BIM)).”
- 3D Semantic Parsing of Large-Scale Indoor Spaces (2016, background): “[40] also employs similar planar surface assumption in order to estimate the semantics of a single room using contextual information.”