A Quaternion-Based Piecewise 3D Modeling Method for Indoor Path Networks

Abstract

Generating 3D path models (with textures) from indoor paths is a good way to improve the visualization performance of 3D indoor path analysis. In this paper, a quaternion-based piecewise 3D modeling method is proposed to automatically generate highly recognizable 3D models for indoor path networks. To create such models, indoor paths are classified into four types of basic elements: corridor, stairs, elevator and node, which contain six kinds of edges and seven kinds of nodes. A quaternion-based method is devised to calculate the coordinates of the designed elements, and a piecewise 3D modeling method is implemented to create the entire 3D indoor path models in a 3D GIS scene. The numerical comparison of 3D scene primitives in different visualization modes indicates that the proposed method can generate detailed and irredundant models for indoor path networks. The result of 3D path analysis shows that indoor path models can improve the visualization performance of a 3D indoor path network by displaying paths with different shapes, textures and colors and that the models can maintain a high rendering efficiency (above 50 frames per second) in a 3D GIS scene containing more than 50,000 polygons and triangles.

An Accurate and Efficient Quaternion-Based Visualization Approach to 2D/3D Vector Data for the Mobile Augmented Reality Map

“…For 3D to 2D line and point correspondences, a novel linear pose estimation based on quaternion is provided, which improves the accuracy and running time of the camera pose estimation algorithm [77]. For visualization of indoor navigation, a quaternion-based precise 3D modeling method for path networks is proposed to automatically generate highly recognizable 3D models [78].…”

Multi‐camera video synopsis of a geographic scene based on optimal virtual viewpoint

“…Since then, the technology of fusion expression and analysis of surveillance videos and geographic scenes has been further studied theoretically and practically. Of the two categories of fusion methods mentioned above—geographic scene‐video image fusion and geographic scene‐video object fusion—the forms of the former include video‐image linkage retrieval analysis (Han et al., 2016) and video projection to geographic scene (Jian, Fan, Liu, Jin, & Kang, 2019; Lewis et al., 2011; Mehboob et al., 2017). Although these methods are relatively easy to implement, they lack analysis and understanding of video image content.…”