Yeting Zhang

Research and practice in three-dimensional city modeling

The way we interact with spatial data has been changed from 2D map to 3D Virtual Geographic Environment (VGE). Three-dimensional representations of geographic information on a computer are known as VGE, and in particular 3D city models provide an efficient way to integrate massive, heterogenous geospatial information and georeferenced information in urban areas. 3D city modeling (3DCM) is an active research and practice topic in distinct application areas. This paper introduces different modeling paradigms employed in 3D GIS, virtual environment, and AEC/FM. Up-to-date 3DCM technologies are evolving into a data integration and collaborative approach to represent the full spatial coverage of a city, to model both aboveground and underground, outdoor and indoor environments including man-made objects and natural features with 3D geometry, appearance, topology and semantics.

Reliable Spatial Relationship Constrained Feature Point Matching of Oblique Aerial Images

Abstract This paper proposes a reliable feature point matching method for oblique images using various spatial relationships and geometrical information for the problems resulted by the large view point changes, the image deformations, blurring, and other factors. Three spatial constraints are incorporated to filter possible outliers, including a cyclic angular ordering constraint, a local position constraint, and a neighborhood conserving constraint. Other ancillary geometric information, which includes the initial exterior orientation parameters that are obtained from the platform parameters and a rough DEM, are used to transform the oblique images geometrically and reduce the perspective deformations. Experiment results revealed that the proposed method is superior to the standard SIFT regarding both precision and correct matches using images obtained by the SWDC-5 system.

A semantics-constrained profiling approach to complex 3D city models

A complex 3D city model contains detailed descriptions of both its appearance and its internal structure, including architectural components. Because of the topological complexity and the large volumes of data in such models, profiling is an effective method to present the internal structure, the distributed characteristics, and the hierarchical relationships of the model to provide intuitive visual information to the viewer and to reveal the relationships between the elements of the model and the whole. However, with commonly used boundary descriptions, it is difficult to comprehensively preserve the consistency of three-dimensional profiling using existing algorithms based on geometric constraints. This paper proposes a novel semantics-constrained profiling approach to ensure the consistency of the geometrical, topological, and semantic relationships when profiling complex 3D city models. The approach transforms the 3D model’s boundary description, defined using the CityGML standard of the Open Geospatial Consortium (OGC), into a set of unified volumetric features described as solids. This approach is characterized by (1) the use of the concepts of semantic relationships, virtual edges, and virtual surfaces; (2) the semantic analysis of 3D models and the extraction of volumetric features as basic geometric analytic units; (3) the completion of structural connectivity and space coverage for each volumetric feature, which is represented as a solid model; and (4) the use of a reliable 3D Boolean operation for efficient and accurate profiling. A typical detailed 3D museum model is used as an example to illustrate the profiling principle, and the experimental results demonstrate the correctness and effectiveness of this approach.

Technical Section: Quantitative analysis of discrete 3D geometrical detail levels based on perceptual metric

Aiming at the fundamental issue of optimal design of discrete levels of detail (LOD) for the visualization of complicated 3D building facades, this paper presents a new quantitative analytical method of perceptible 3D details based on perceptual metric. First, the perceptual metric is defined as the quantitative indicator of the visual perceptibility of facade details at a given viewing distance. Then, according to the human vision system, an algorithm employing 2D discrete wavelet transform and contrast sensitivity function is developed to extract the value of perceptual metric from the rendered image of the facade. Finally, a perceptual metric function is defined, based on the perceptual metric values extracted at equal interval viewing distances. The minimum detail redundancy model is then proposed for the optimal design of discrete LODs. This method provides a quantitative instruction for generating discrete LODs. The experimental results prove the effectiveness and great potential of this method.

An Efficient Point Cloud Management Method Based on a 3D R-Tree

Vehicle-borne laser-scanned point clouds have become increasingly important 3D data sources in fields such as digital city modeling and emergency response management. Aiming at reducing the technical bottlenecks of management and visualization of very large point cloud data sets, this paper proposes a new spatial organization method called 3DOR-Tree, which integrates Octree and 3D R-Tree data structures. This method utilizes Octrees rapid convergence to generate R - T ree leaf nodes, which are inserted directly into the R - T ree, thus avoiding time-consuming point-by-point insertion operations. Furthermore, this paper extends the R - T ree structure to support LOD (level of detail) models. Based on the extended structure, a practical data management method is presented. Finally, an adaptive control method for LODS of point clouds is illustrated. Typical experimental results show that our method possesses quasi-real-time index construction speed, a good storage utilization rate, and efficient visualization performance.

Towards Semantic 3D City Modeling and Visual Explorations

In recent years, the integration of semantics into 3D city models has become a consensus. The CityGML standard laid the foundation for the storage and application of semantics, which boosts the progress of semantic 3D city modeling. This paper reports an extended semantic model based on CityGML and its visual applications under the content of a three-dimensional GIS project of China. Firstly, concepts Room, Corridor and Stair are derived from concept Space which represents the similar concept of Room in CityGML. These concepts will benefit the application of indoor navigation. Geological model is also supported by this model, which enables the underground analysis. Secondly, a semi-automatic data integration tool is developed. The types of semantic concept are defined based on the Technical Specification for Three-Dimensional City Modeling of China which leads to an adaptive way to assign semantics into pure geometry. In order to better visualize the models enriched by semantics, two fundamental techniques, data reduction and selective representation are then introduced. It shows that semantics could not only help improve the performance of exploration tasks but also enhance the efficiency of spatial cognition. Finally, two exploration cases are presented, one is indoor navigation, the semantic model is used to extract the geometric path and a semantics enhanced navigation routine is used, which greatly enriches the connotation of ordinary navigation applications; the other is a unified profiler, in order to fill up the cross-section correctly, semantics are incorporated, which help ensure the topological and semantic consistency.

A hybrid spatio-temporal data indexing method for trajectory databases.

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

A Flexible Method for Zoom Lens Calibration and Modeling Using a Planar Checkerboard

This paper presents a fl exible method for zoom lens calibration and modeling using a planar checkerboard. The method includes the following four steps. First, the principal point of the zoom-lens camera is determined by a focus-of-expansion approach. Second, the infl uences of focus changes on the principal distance are modeled by a scale parameter. Third, checkerboard images taken at varying object distances with convergent image geometry are used for camera calibration. Finally, the variations of the calibration parameters with respect to the various zoom and focus settings are modeled using polynomials. Three different types of lens are examined in this study. Experimental analyses show that high precision calibration results can be expected from the developed approach. The relative measurement accuracy (accuracy normalized with object distance) using the calibrated zoom-lens camera model ranges from 1:5 000 to 1:25 000. The developed method is of signifi cance to facilitate the use of zoom-lens camera systems in various applications such as robotic exploration, hazard monitoring, traffi c monitoring, and security surveillance.

Design and Implementation of 3D Model Database for General-Purpose 3D GIS

To improve the reusability of three-dimensional (3D) models and simplify the complexity of natural scene reconstruction, this paper presents a 3D model database for universal 3D GIS. After the introduction of its extensible function architecture, accompanied by the conclusion of implicit spatial-temporal hierarchy of models in any reconstructed scene of 3D GIS for general purpose, several key issues are discussed in detail, such as the storage and management of 3D models and related retrieval and load method, as well as the interfaces for further on-demand development. Finally, the validity and feasibility of this model database are proved through its application in the development of 3D visualization system of railway operation.

GeoScope: Full 3D geospatial information system case study

Aiming at the integrative management and comprehensive applications of large-scale 3D geospatial information covering the full 3D space of a city, this paper briefly introduces the design and implementation of a full 3D GIS platform: GeoScope, which provides a professional solution for the massive full three-dimensional geospatial data integration, management, analysis, visualization, and applications. GeoScope is characterized by: (1) extendible software architecture based on the hierarchical message bus, facilitates multimodal integrative applications of 2D GIS and 3D GIS; (2) unified 3D city models, support multiscale semantic representation of outdoor & indoor and aboveground & underground 3D objects; (3) high-efficient 3D geospatial database engine, supports integrated management of massive 3D geospatial data for real-time applications; and (4) high-performance visualization engine exploiting the massively parallel computation architecture of modern GPUs, supports real-time realistic rendering of large-scale complicated 3D geospatial environments. The successful pilot application of GeoScope is also illustrated with the 3D city models of 8494 km2 of the whole Wuhan City, the largest city in middle China.