Modeling Surperspective Projection of Landscapes for Geographical Guide-Map Generation

Abstract

It is still challenging to generate hand‐drawn pictures because they differ from ordinary photographs in that they are often drawn as seen from multiple viewpoints. This paper presents a new approach for modeling such surperspective projection based on shape deformation techniques. Specifically, surperspective landscape images for guide‐maps are generated from 3D geographical elevation data. Our method first partitions a target geographical surface into feature areas to provide designers with landmarks suitable for editing. The system takes as input 2D visual effects, which are converted to 3D geometric constraints for geographical surface deformation. Using ordinary perspective projection, the deformed shape is then transformed into a target guide‐map image where each landmark enjoys its own vista points. An algorithm for calculating such 2D visual effects semi‐automatically from the geographical shape features is also considered.

Generalized projection for yamato-e and ukiyo-e with projection reference plane

“…Kubo et al [7] mentioned Ukiyo-e projection in the context of multi-perspective projection [3,10,13]. However, the characteristics of linearity and verticality are not explicitly discussed.…”

Occlusion-Free Visualization of Important Geographic Features in 3D Urban Environments

“…However, the distortions introduced by occlusion-removal methods are always a major concern. Takahashi et al [12] developed a system for creating panoramic maps that enhances the visibility of important roads and landmarks. Later, they proposed an occlusion-free route animation for car navigation in mountainous areas [9].…”

“…Zhang et al's method [12] is adopted to extract the urban pattern. To extract the urban spatial pattern, we consider a range of scales from a global aspect to local features.…”

“…We extract the distribution pattern of the buildings as well as local alignment groups in the pattern. For the distribution pattern, we construct a proximity graph to represent the clusters and relations among buildings in each block [12]. For the local alignment, we extract the alignment groups based on the gestalt rules [12,23] and associate the groups with the graph.…”

Automatic Generation of 2.5D Terrain Models without Occluding Routes of Interest

“…Qu et al (2009) presented a focus plus context zooming technique to broaden the occluded roads with other context being maintained. Meanwhile, Takahashi et al (2002) presented an approach for generating panorama guide-maps, which can calculate the landscape displacement and rotation semi-automatically. However, all these approaches are not capable of producing panoramic views automatically.…”