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1.	Mao, Bo, 1983-, et al. (författare) Detection and typification of linear structures for dynamic visualization of 3D city models 2012 Ingår i: Computers, Environment and Urban Systems. - : Elsevier BV. - 0198-9715 .- 1873-7587. ; 36:3, s. 233-244 Tidskriftsartikel (refereegranskat)abstract Cluttering is a fundamental problem in 3D city model visualization. In this paper, a novel method for removing cluttering by typification of linear building groups is proposed. This method works. in static as well as dynamic visualization of 3D city models. The method starts by converting building models in higher Levels of Details (LoDs) into LoD1 with ground plan and height. Then the Minimum Spanning Tree (MST) is generated according to the distance between the building ground plans. Based on the MST, linear building groups are detected for typification. The typification level of a building group is determined by its distance to the viewpoint as well as its viewing angle. Next, the selected buildings are removed and the remaining ones are adjusted in each group separately. To preserve the building features and their spatial distribution, Attributed Relational Graph (ARC) and Nested Earth Mover's Distance (NEMD) are used to evaluate the difference between the original building objects and the generalized ones. The experimental results indicate that our method can reduce the number of buildings while preserving the visual similarity of the urban areas. (C) 2011 Elsevier Ltd. All rights reserved.

Mao, Bo, 1983-, et al. (författare)
Detection and typification of linear structures for dynamic visualization of 3D city models
2012
Ingår i: Computers, Environment and Urban Systems. - : Elsevier BV. - 0198-9715 .- 1873-7587. ; 36:3, s. 233-244
Tidskriftsartikel (refereegranskat)abstract
- Cluttering is a fundamental problem in 3D city model visualization. In this paper, a novel method for removing cluttering by typification of linear building groups is proposed. This method works. in static as well as dynamic visualization of 3D city models. The method starts by converting building models in higher Levels of Details (LoDs) into LoD1 with ground plan and height. Then the Minimum Spanning Tree (MST) is generated according to the distance between the building ground plans. Based on the MST, linear building groups are detected for typification. The typification level of a building group is determined by its distance to the viewpoint as well as its viewing angle. Next, the selected buildings are removed and the remaining ones are adjusted in each group separately. To preserve the building features and their spatial distribution, Attributed Relational Graph (ARC) and Nested Earth Mover's Distance (NEMD) are used to evaluate the difference between the original building objects and the generalized ones. The experimental results indicate that our method can reduce the number of buildings while preserving the visual similarity of the urban areas. (C) 2011 Elsevier Ltd. All rights reserved.

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