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Real-time visualization of 3D city models at street-level based on visual saliency
KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatics.
Lund University.
2015 (English)In: Science China Earth Sciences, ISSN 1674-7313, Vol. 58, no 3, 448-461 p.Article in journal (Refereed) Published
Abstract [en]

Street-level visualization is an important application of 3D city models. Challenges to street-level visualization include the cluttering of buildings due to fine detail and visualization performance. In this paper, a novel method is proposed for street-level visualization based on visual saliency evaluation. The basic idea of the method is to preserve these salient buildings in a scene while removing those that are non-salient. The method can be divided into pre-processing procedures and real-time visualization. The first step in pre-processing is to convert 3D building models at higher Levels of Detail (LoDs) into LoD1 models with simplified ground plans. Then, a number of index viewpoints are created along the streets; these indices refer to both the position and the direction of each street site. A visual saliency value is computed for each building, with respect to the index site, based on a visual difference between the original model and the generalized model. We calculate and evaluate three methods for visual saliency: local difference, global difference and minimum projection area. The real-time visualization process begins by mapping the observer to its closest indices. The street view is then generated based on the building information stored in those indexes. A user study shows that the local visual saliency method performs better than do the global visual saliency, area and image-based methods and that the framework proposed in this paper may improve the performance of 3D visualization.

Place, publisher, year, edition, pages
2015. Vol. 58, no 3, 448-461 p.
Keyword [en]
3D city models, street level visualization, index viewpoints, visual saliency
National Category
URN: urn:nbn:se:kth:diva-162948DOI: 10.1007/s11430-014-4955-8ISI: 000349767600012ScopusID: 2-s2.0-84925491759OAI: diva2:800190

QC 20150402

Available from: 2015-04-02 Created: 2015-03-26 Last updated: 2015-06-22Bibliographically approved

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Ban, Yifang
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