GeoSensor Networks - Chapter 9

Generation and Application of Virtual Landscape Models for Location-Based services Norbert Haala and Martin Kada Institute for Photogrammetry (ifp), University of Stuttgart, Germany Geschwister-Scholl-Strasse 24D, D-70174 Stuttgart Norbert.Haala@ifp.uni-stuttgart.de ABSTRACT The efficient collection and presentation of geospatial data is one key task to be solved in the context of location based services. As an example, virtual landscape models have to be generated and presented to the user in order to realize tasks like personal navigation in complex urban environments. For an efficient model generation, different data sources have to be integrated, whereas an efficient application for location based services usually requires the use of multiple sensor configurations. The work on the generation and application of virtual landscape models described within the paper is moti-vated by a research project on the development of a generic platform that supports location aware applications with mobile users. 1. INTRODUCTION The ongoing rapid developments in the field of computer graphics meanwhile allow the use of standard hard- and software components even for challenging tasks like the real-time visualization of complex three-dimensional data. As a result, components for the presentation of structured three-dimensional geo-data are integrated in an increasing number of applications. If virtual three-dimensional landscapes and building models – both indoor and outdoor – are visualized three-dimensionally, the access to spatial information can for ex-ample be simplified within personal navigation systems. In order to realize these type of applications, 3D landscape models have to be made available as a first step and tools allowing for the efficient presentation of this data have to be provided. Within the paper, we present our work on the generation and application of virtual landscape models. These algorithms were developed as a part of the Nexus project, which was started at the University of Stuttgart, Germany, with the goal of developing concepts and methods for the support of mobile and location-based applications. Meanwhile, this project has been extended to the interdisciplinary center of excellence “World Models for Mobile Context-Aware Systems”, covering issues concerning communication, information management, methods for model representation and sensor data integration Copyright © 2004 CRC Press, LLC (Stuttgart University 2003). One of the long term goals of this project is the development of concepts and techniques for the realization of comprehensive and detailed world models for mobile context-aware applications. In addition to a representation of stationary and mobile objects of the real world these world models can be augmented by virtual objects, and objects of the real world can be linked to additional information. The result is the so-called "Augmented World Model", which is an aggregated model of the real world and a symbiosis of the real world and digital information spaces. The com-plexity of these world models ranges from simple geometric models, to street maps and to highly complex three-dimensional models of buildings. In the following section, the data collection for the virtual landscape model, which is used as a basis for our investigations is described. In the second part of the paper, the visualization of this model and data access is discussed. 2. DATA COLLECTION For our investigations a detailed virtual landscape world model of the city of Stuttgart and the surrounding area of the size 50x50km was made available. The data set includes a 3D city model, a digital terrain model and correspond-ing aerial images for texture mapping. 2.1 Integration of existing data Since the development of tools for the efficient collection of 3D city mod-els has been a topic of intense research in recent years, meanwhile a number of algorithms based on 3D measurement from aerial stereo imagery or air-borne laser scanner data are available. A good overview on the current state-of-the-art of experimental systems and commercial software packages is for example given in (Baltsavias, Grün, van Gool 2001). Due the availability of these tools a number of cities already provide area covering data sets, which include 3D representations of buildings. For our test area, a 3D city model was collected on behalf of the City Sur-veying Office of Stuttgart semi-automatically by photogrammetric stereo measurement from images at 1:10000 scale (Wolf 1999). For data collection, the outline of the buildings from the public Automated Real Estate Map (ALK) was additionally used. Thus, a horizontal accuracy in the centimeter level as well as a large amount of detail could be achieved. The resulting model contains the geometry of 36,000 buildings represented by 1.5 million triangles. In addition to the majority of relatively simple buildings in the sub-urbs, some prominent historic buildings in the city center are represented in detail by more than 1,000 triangles each. An overview visualization based on the available data is given in Figure 1. Copyright © 2004 CRC Press, LLC Figure 1: Overview of the Stuttgart city model covering a total of 36,000 building models. 2.2 Texture Mapping Image texture for visualizations similar to Figure 1 is usually provided from ortho images, which can be collected by airborne or spaceborne sensors. For visualizations from pedestrian viewpoints, like they are required for naviga-tion applications, the visual appearance of buildings has to be improved. For this reason, façade texture was additionally collected for a number of build-ings in the historic central area of the city. Whereas ongoing research aims at automating of this process, within the first phase of the project manual map-ping was applied for this purpose. 2.2.1 Manual Mapping This manual mapping of the facades was based on approximately 5,000 ter-restrial images collected by a standard digital camera. From these images, which were available for approximately 500 buildings, the façade textures were extracted, rectified and mapped to the corresponding planar segments of the buildings using the GUI depicted in Figure 2. Copyright © 2004 CRC Press, LLC Figure 2: GUI for manual texture mapping of façade imagery. This GUI allows the user an easy selection of corresponding points at the façade and the respective images. Based on this information the effects of perspective distortion are eliminated by a rectification and the resulting image is then initially snapped to the corresponding part of the building model to be textured. A precise adjustment of the final texture coordinates is then realized by a user controlled affine transformation. Finally, in order to reduce the partly large size of the original images, the texture images are down-sampled to a resolution of approximately 15 cm per pixel at the facades. Figure 3: Rendered view of textured building models. Copyright © 2004 CRC Press, LLC A visualization based on the result of manual texture mapping is depicted in Figure 3. In this example additionally random colors were assigned for buildings in the background of the scene, were no real image texture from manual mapping was available. 2.2.2 Panoramic images One option to provide real image texture at lower quality, but a reduced effort compared to manual mapping is the application of panoramic images. For this purpose we used the high resolution digital panoramic camera TOPEYE, originally developed as a measurement system for photogrammetric purposes (Scheibe et al. 2001). Based on a CCD line, which is mounted on a turntable parallel to the rotation axis, high resolution 360 degree panoramic images can be generated. In order to reach the highest resolution and a large field of view, a CCD line with about 10.000 detector elements is used. The second image dimension is generated by rotating the turntable. Since this CCD is a RGB triplet it allows for the acquisition of true color images. Figure 4: Image collected by the panoramic camera EYESCAN. Figure 4 depicts a complete scene collected by the panoramic camera from the top of a building. The enlarged section demonstrates the high resolu-tion, which can be reached by this type of camera. If as in this example, the scene gives a good overview of a larger area, texture mapping is feasible for a number of buildings at least with a limited amount of detail. If the exterior orientation of the panoramic image is available, this can be realized automati-cally similar to the generation of ortho images. In order to determine the re- Copyright © 2004 CRC Press, LLC ... - tailieumienphi.vn