Autostereoscopic 3D-Geovisualisation of Crime Scene Allocations

Transcription

1 Autostereoscopic 3D-Geovisualisation of Crime Scene Allocations Dirk STENDEL and Markus WOLFF Abstract This paper presents an approach to create three-dimensional autostereoscopic visualisations for the purpose of communicating crime analysis related information to a broad audience. The increasing complexity of planning processes often leads to a heterogeneous mixture of participants with different visual interpretation skills. Investors, local councillors, planners, experts and citizens, they all are involved (BENDFELDT & BENDFELDT, 2002; WARREN- KRETSCHMAR & TIEDKE, 2005). Commonly, the results of geospatial crime data analysis are published to the targetaudience by using traditional two-dimensional thematic maps. Therefore cartographic visualisations can be considered as a key element. According to the defined task and the analysed crime, the generated maps vary in subject, purpose, audience and map quality. Depending on the map topic and target audience, these maps may be difficult to comprehend. The main objective of the presented research project is an increase in the comprehensibility and an improved interpretation of visualisations related to geospatial crime scene analysis by the use of autostereoscopic techniques. Especially lay people are considered as the target audience. Advantages of this presentation technique which are due to the psychology of perception and positive results of an evaluation of the spatial techniques' acceptance legitimize this approach (HERSHENSON, 1999; STENDEL, 2009a; b).this paper will demonstrate a procedure of combinating approaches of three-dimensional geo-visualisation with an innovative technique, which allows an autostereoscopic paper based visualisation on the basis of lenticular plates (virtual-lenticular-rendering-method, VLR-method).This is realised by applying a twofold work flow. In a first step, crime scene allocations are analysed by applying methods of geo-information science. In a second step the results are pre-processed and passed to an autostereoscopic imaging process. Geospatial analysis therefore begins with analyzing geospatial allocations of robbery scenes. This dataset is provided by the police headquarter of the German city of Cologne. Enhanced by a number of further geospatial datasets, the findings of this analysis generate three-dimensional visualizations of tactical intelligence assessments (WOLFF, 2009). In a subsequent step, selected parts of such an intelligence assessment are passed to an autostereoscopic imaging process and are finally prepared for printing. An inflexible lenticular plate is used to decipher the printed, visually incomprehensible base image. Result is an autostereoscopic image of considerable visual spatial depth (BOURKE, 1999; BUCHROITHNER, 2007). The VLR-method first encodes the available three-dimensional data object-specifically. The subsequent appliance of the lenticular plate results in the decoding of an apparently threedimensional space. The presented information regarding criminal action allocation of the spatial image may be easily interpreted even by untrained map readers (STENDEL, 2009a; b). These results get the project a step closer to the overall research objective and describe

2 192 D. Stendel and M. Wolff the experience gained using the VLR-method as a post-analytical, nearly contentindependent autostereoscopic data preparation tool. The results presented may as well be assigned to different fields of space-oriented data visualisation. Consequently, this paper describes a pilot project in the practice-oriented and multidisciplinary application of the lenticular technique using the VLR-method. 1 Introduction In the field of landscape architecture varying research projects have been conducted over the past years which had an objective of stereoscopic and autostereoscopic presentation techniques creating the impression of spatial depth (PAAR ET AL., 2004; ZEHNER, 2008; 2009). An emphasis of autostereoscopic methods was placed on the lenticular technique, especially combined with the VLR-method (cf. STENDEL, 2008a). The quality of visualisations created with this technique and the impact of the spatial depth was evaluated. A high degree of acceptance could be attested as well as an explicit increase in comprehension of the presented contents compared to comparable two-dimensional visualisations. An above-average positive response by people outside of the subject area could be noted (STENDEL, 2009b). These results motivated the examination of other fields of visualisation for similar acceptability in this case the visualisation of criminal action allocations. This scope of application is especially characterised by the common interest in the presented information throughout different user groups without a subject-specific background. It is to be expected that an autostereoscopic presentation technique will have a positive effect on the approachability and comprehensibility for the users. The spatial impact and related comprehensibility of the lenticular technique ranges between the effects of a two-dimensional perspective and a physical three-dimensional model. Being a paper based, two-dimensional presentation media, a lenticular image achieves a graphical and spatial quality formerly restricted to physical three-dimensional models, which leads to advantages in the comprehensibility of lay people (RASE, 2007). Compared to such a 3dmodel it may be produced rather quickly and inexpensively, though. The required hardware may be used repeatedly. The merit of physical three-dimensional models in the context of thematic cartography is known and described extensively (RASE, 2003; 2007; 2009). 2 Geospatial Crime Scene Analysis and Visualisation Considering the geospatial analysis of crime scenes, geographic information systems (GIS) can be considered as an adequate tool for managing and analysing crime data (CHAINEY & RATCLIFFE, 2005; MURRAY ET AL., 2001). To communicate the results of analysis to a broader audience thematic two-dimensional static maps are widely used. Frequently these maps show pattern or feature distributions, for instance the spatial variation of crime hotspots related to certain offences. However, particularly decision makers or the public readers are not trained in reading complicated maps. The creation of intuitive threedimensional visualisations can be considered as a promising tool for supporting an instant grasp of complex analysis results to a broader audience (experts and laymen), as, for instance, in the context of crime-preventive urban planning. By applying methods of 3D

3 Autostereoscopic 3D-Geovisualisation of Crime Scene Allocations 193 geo-visualisation, the presented approach aims therefore at visualizing crime related issues in paper based and three-dimensional format. By using the example of robbery crimes within the German city of Cologne in a first step geospatial analysis is conducted to derive spatial patterns of urban crime scene densities (for the year 2007). For geospatial analysis and initial 3D visualisation the following workflow is applied within this study: at first geo-coded crime scene data is processed and analysed with GIS methods. Against this background density mapping techniques using kernel density estimations (KDE) are applied to identify and map hotspots of robbery crimes (WOLFF & ASCHE, 2009). Although different kernel density functions exist (SMITH, GOODCHILD & LONGLEY, 2006), each KDE-algorithm eventually results in a grid whose cell values represent density values (of incidents per a defined surface unit of measure). By using this technique the discrete point-based information of robbery scene positions is transformed to a continuous surface that represents density values for each single grid cell. In a next step this geo-statistical surface is passed to the LandXplorer system for 3D visualisation. At this point the 3D surface can be overlaid with further geo-coded textures as for instance with choropleth maps of the hotspot grid or with topographic maps (cf. Fig. 1). Actually, this method is predominately used to create fixed and paper based 3D visualisations but prepared for a digital real-time application, too. Fig. 1: 2D KDE surface (left-hand image) and respective 3D representation of robbery scene densities within the city of Cologne in Benefits of Autostereoscopic Picture Conversion The procedure described in chapter 2 (geospatial crime scene analysis and development of explanatory visualisations) is independent of the further appliance of the VLR-method. The resulting static illustrations may be viewed and interpreted by the observer. With respect to image analytical aspects and aspects of psychology of perception several image areas provide an opportunity for misinterpretation (RASE, 2003; 2007).

4 194 D. Stendel and M. Wolff Fig. 2: Occlusion effects in 3D robbery hotspot surface The human vision uses different depth cues for the interpretation of spatial information. Those depth cues are of differing impact and may be combined in several ways. Generally, the more depth cues are presented, the more definite they may be interpreted by the observer (HUBONA ET AL., 1999). Figure 2 shows a variety of depth cues also available for two-dimensional images. Occlusions, object and cast shadows as well as linear perspective information support the spatial perception and applied to Fig. 2. These effects are the most effective of the twodimensional (GOLDSTEIN, 2002; HERSHENSON, 1999). In some cases, these do not sufficiently explain a complex spatial situation. With fixed viewing points as in Fig. 2, object overlap may lead to an ambiguous perception (cf. RASE, 2007). The areas in question are marked in red. E. g. in the right-hand part of Fig. 2 it is unclear, whether one single or many closely succeeding hot-spots are displayed. The choice of viewpoint and interaction of colours may lead to ambiguous sections in two-dimensional images. In a stereoscopic image, additional parallax information is provided which facilitates a separate optical perception of succeeding hot-spots. Further depth cues may be integrated with the lenticular technique via the VLR-method (disparities and motion parallaxes), so the image comprehensibility is increased, which is especially helpful for untrained observers (RASE, 2007; STENDEL, 2008a; 2009a). On the other hand approximately five percent of humans are not able to interpret disparities (e.g. strabismus) (VALJUS, 1966). Yet another increase of comprehensibility may be achieved with physical three-dimensional models. In addition to optical information and a free choice of viewpoint the observer is provided with tactile information (RASE, 2009).

5 Autostereoscopic 3D-Geovisualisation of Crime Scene Allocations 195 Fig. 3: Part of the used z-depth image representing the robbery hotspot surface 4 Practice The discrete allocations of robbery scenes are processed as described in chapter 2. The resulting images may be reprocessed to become autostereoscopic images. Presently, this is achieved with the software 3D-Studio Max. Data conversion processes are necessary due to a lacking implementation of the VLR-method in 3D-Studio Max and due to the lack of a stereoscopic data export interface in the software LandXplorer which is used as well. 4.1 Workflow Currently, the use of the VLR-method within the LandXplorer software is not possible; no plug-in solution has been developed, yet. Moreover the data of the spatial grid system shown in Figure 1-2 and displayed by the LandXplorer may not be exported directly. Therefore, the data used in this project were customised for the VLR-method with the software ArcGIS and then exported. The density allocation of the crime spots was transformed to a greyscale picture, which was used as a depth image (z-depth image) in the following process (cf. FEHN, 2006). The 256 greyscales represent the altitudinal series developed in LandXplorer (see Fig. 3). This image may be used with 3D-Studio Max in order to construct the surface geometry of the scene. The camera position in LandXplorer is defined via coordinates and may therefore be reconstructed in 3D-Studio Max. The value of the camera viewing angle may not be obtained; therefore it was reconstructed by approximation. 4.2 VLR-method Starting basis for the VLR-method is a 3d-computer model which has been reconstructed in the visualisation software 3D-Studio Max as described before (chapter 3.2). Within this model, a virtual surface is constructed and positioned between the 3d-scene (3d-geometry) and the scene camera position. The virtual surface is an auxiliary construction and equals the surface of the lenticular plate which will be used in the last step of the process. A specific refraction index is used for rendering the base image in a single process (see Fig. 4).

6 196 D. Stendel and M. Wolff Fig. 4: Base image created with the VLR-method The refraction index of the virtual plane is obtained by use of a specialized algorithm developed by the author (cf. STENDEL, 2008b). The related stereoscopic parameters near point and far point of the 3d-scene, camera position and viewing distance are incorporated (cf. ALBERTZ, 2007; PIETSCH, 1959; WAACK, 1982). The parameters of the present example model were used to calculate a refraction index of n=0,914. A common scanline rendering algorithm is used to convert the 3d-scene geometry into the base image which is then printed (Fig. 4). The current mode of operation is still very complex and not automated, therefore the process is relatively time consuming and error-prone. An auto stereogram is achieved with the appliance of a lenticular plate on top of the image. In this example a lenticular plate of 10 lpi (lenses per inch) was used (Fig. 5). The resulting visible picture quality allows the observer to read the street names and other important map information (orig. picture size is 15 by 7 cm). Fig. 5: Visible autostereoscopic picture reconstructed from Fig. 4 (photograph)

7 Autostereoscopic 3D-Geovisualisation of Crime Scene Allocations Conclusions This paper demonstrated an approach to combine geospatial crime scene analysis with the visualisation potential of an autostereoscopic imaging method. The overall aim of this work was to design innovative visualisations that help to communicate geospatial analysis results in an easy-to-comprehend way primarily for the GIS-untrained laymen of a broader public. Up to now the processing of autostereoscopic illustrations of distribution patterns of robbery crime scenes is laborious and takes a great amount of manual work. One reason is the lacking support of stereoscopic export interfaces (z-buffering) within VIS-software (here: LandXplorer), another is the lacking implementation of the VLR-method in established 3d-visualisation software (e. g. 3D-Studio Max). Despite these facts it is possible to create a visualisation of acceptable quality in approx. six hours of working time (2.5 hours of converting, 3.5 hours for the VLR-method and the rendering process). These visualisations are ready for evaluation and will be presented to different user groups in the near future. It is unknown, whether the high acceptance and attested improved comprehension within the field of landscape architecture may be assigned to the field of visualisation of crime allocation. At the current state of knowledge, a validation or relativization is not possible. The next step will be the presentation of the created autostereograms to a broad audience from different fields of practice. Should the current state of knowledge be confirmed in the course of further research, the directly implementation of the VLR-method into geovisualisation software is the next implication and will be further investigated and promoted. 6 Acknowledgements The further development of the VLR-method is funded by the German Federal Ministry of Education and Research (BMBF) and is associated with the research program ForMaT. The project title is: Autostereoskopische Produktlösung auf Basis der VLR-Methode (cf. I%282%29.pdf). Funding of the crime mapping related part of this study by the German Federal Ministry of Education and Research (BMBF) within the framework of the InnoProfile research group 3D Geoinformation ( is gratefully acknowledged. The authors also like to thank the police headquarters of the city of Cologne for providing extensive burglary crime datasets. Furthermore the authors give a special thanks to the municipality of the city of Cologne and to Virtual City Systems, Inc. for providing the 3D city model and other geospatial base data. Finally, the authors thank Autodesk, Inc. for supplying the LandXplorer system.

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