Method and device for pictorial representation of space-related data

Abstract

A method and device for the pictorial representation of space-related data, for example, geographical data of the earth. Such methods are used for visualising topographical or meteorological data in the form of weather maps or weather forecast films. Further fields of application are found in tourism, in traffic control, in navigation aids and also in studio technology. The space-related data, for example topography, actual cloud distribution, configurations of roads, rivers or frontiers, satellite images, actual temperatures, historical views, CAD-models, actual camera shots, are called up, stored or generated in a spatially distributed fashion. For a screen representation of a view of the object according to a field of view of a virtual observer, the required data are called up and shown only in the resolution required for each individual section of the image. The sub-division of the image into sections with different spatial resolutions is preferably effected according to the method of a binary or quadrant tree.

Description

The invention relates to a method and a device for pictorial representation of space-related data, particularly geographical data of flat or physical objects. Such methods are used for example for visualising topographic or meteorological data in the form of weather maps or weather forecast films. Further fields of application arise from tourism, in traffic control, as navigation aids and in studio technology.

Representations of geographical information are generated according to prior art by using a so-called paintbox. The latter generates from given geographical information maps of a desired area, which are then selectably altered, and for example can be coloured or emphasised according to states, or even represented in an altered projection.

Another system for generating views of a topography is found in the known flight , 00,000 texturised triangles per second and consequently is suitable for rapid picture build-up. It operates with floating-point views with a 32 bit representation. As this accuracy in the present example is insufficient for example to follow a movement of an observer from space continuously down to a centimetre resolution on the earth, the co-ordinates of the data during such a movement were continuously converted to a new co-ordinate system with a coordinate origin located in the vicinity of the observer.

The geographical data required for the image are called up and transmitted via the collecting network 6 from the spatially distributed memories 4. The spatially distributed memories are preferably located in the vicinity of the areas on the earth whose data they contain. In this way the data are detected, stored and serviced at the point where a knowledge of the properties to be represented by the data, such for example as topography, political or social information, etc. is most precise. Further data sources are located at the points where further data are detected or assembled, such for example as meteorological research stations which collect and process information received from satellites.

A characteristic feature of the data flow in the collector network 6 is that the data flow is in one direction. The Internet or ISDN lines were used for this network.

The interchange network 7 serves to interchange data between individual nodes. By means of close-meshed connection of the individual nodes, the network can be secured against the failure of individual conduits or against load peaks. As the interchange network 7 must guarantee a high transmission rate in both directions, a permanent connection was used here with an asynchronous transmission protocol with a transmission rate which is greater than 35 MBit/s. Satellite connections are also suitable for the interchange network 7.

In the supply network 8, substantially the image data required for representation are transmitted to the display device 5. Consequently a high data transmission rate of up to 2 MBit/s is required in the direction of the display unit, which is enabled by intrinsic asynchronous connections or by bundling ISDN connections.

FIG. 2 shows two nodes connected by an interchange network 7, a primary node 1 and a tertiary node 3. An input medium 10 for input of the location and the direction of view of the observer is connected via the supply network 8 to the tertiary node 3. A collector network 6 and a camera 9, which can be controlled by the input medium 10, is connected to the node computer 1. The input medium 10 comprised consists of a three-dimensional track ball in conjunction with a space-mouse with six degrees of freedom, in order to be able to alter both the location and the direction of view of the observer. Automatic position-fixing systems can also be considered as further input media, such as are used in navigation aids for motor vehicles or aircraft.

In this embodiment given by way of example, a two-dimensional polygon grid model is used to display the data, which serves as a two-dimensional co-ordinate system for positioning the data. There were used as data to be displayed, for example satellite images, i.e. information relating to the colouring of the earth surface or geopolitical data or actual or stored meteorological data. Images of the same point on the earth surface were shown at different points in time, so that a type of “time journey” could be produced.

Data in tabular form, such for example as temperature information, were masked in as display tables into the view. For certain areas, CAD-models of buildings were available, which were inserted into the view. Then the location of the observer could be displaced at will in these CAD-modelled buildings.

Via position-fixing systems, symbols, for example for ships, aircraft or motor vehicles, in their instantaneous geographical positions, can be inserted into this system and/or animated.

There was used, as a model for sub-dividing the field of view into sections and of these sections into further sections, a quadrant tree in which a progressive sub-division of an area into respectively four sections is carried out.

After selection of the earth as an object and input of a location and a direction of view in the final device 5, the node 3 determines the field of view of the observer and calls up the data via the interchange network 7 and the nodes 1 and 2. These nodes in turn call up, via the collecting network 6, from the spatially distributed data sources 4 or for example from the camera 9, the required data and transmit them over the interchange network 7 to the node 3 for central storage. The node 3 determines the representation of the data centrally stored therein and sends this transmission for viewing over the supply network 8 to the display device 5.

If the node 3 then ascertains that the required screen resolution has not been achieved with the centrally stored data, it divides the field of view according to the model of the quadrant tree into four sections and checks each section to see whether, by representation of the data contained in the sections, the required image resolution has been achieved. If the required image resolution is not achieved, the node 3 calls up further data for this section. This method is repeated for each section until the required image resolution is achieved in the entire view. Call-up of the data is effected in this example always with the same resolution of 128×128 points. Due to the sub-division of a section into four respective sub-sections, therefore, in each data transmission data are loaded which have a spatial accuracy four times higher.

FIG. 3 shows diagrammatically the view of an object 18 by an observer whose field of view is limited by the two lines 17. As the pictorial representation remains the same, the required spatial resolution of the data depends on its distance from the observer. For objects located directly in front of the observer, data must be available with a greater spatial resolution than for objects further removed, in order to reach this image resolution.

FIG. 3 shows in all four different sub-division stages according to the model of the quadrant tree. The object entered extends within the field of view over three resolution stages in all. The data for the area of the object belonging to the field of view must therefore be loaded with greater spatial resolution in the direction of the observer.

By virtue of the fact that the data are centrally stored in sections only in the accuracy required for image resolution, the number of centrally stored data depends substantially only on the desired image resolution.

If for example one is located approximately 1,000 m above the earth surface, the field of view has an extent of approximately 50 km×50 km. The image resolution in this case should be greater than 3,000×3,000 image points. In order to show the field of view with this image resolution a height value is required every 150 m and an image value of a surface every 15 m. From this there arises a central storage requirement of approximately 35.6 MBytes, in order to store all the required information for showing the image.

If however one is located in space and has the northern hemisphere fully in field of view, then there is required for a representation with the same image resolution a height value every 50 km and an image value of the surface every 5 km. In all there arises a central storage requirement of 39.2 MBytes, which lies in the same order of magnitude as the storage requirement for representation of the view of the earth surface from a height of 1,000 m in the section 50 km×50 km.

FIG. 4 shows the formation of an address of a section using the model of a quadrant tree for sub-division of the field of view 11. In the first sub-division of the field of view 11 into four sections 12, these are identified clockwise with the numerals 0 to 3. If a section is further sub-divided, the individual sub-sections 13 are numbered in the same way and the numbers thus obtained are prefixed to the numbers of the master section. With a permanently identical resolution of for example 128×128 points per section, the number of points of the section number is at the same time an indication of the level of spatial precision of the data.

An advantage in this type of address formation is further that each section of the object to be represented has a fixed address which to a great extent simplifies the search for the associated data.

FIG. 5 shows how a binary tree can be mixed with a quadrant tree in order to generate an adaptive sub-division model. In the upper row of the squares the sub-division is shown in two slave sections 4 and 5 (vertical) or 6 and 7 (horizontal). In the lower part of the drawing there is shown a further sub-division of the section 4 into an elongate upper portion 46 and two lower portions 40 and 43. The section 33 43 is then again sub-divided according to the model of a quadrant tree into four slave sections. Such an adaptive sub-division model can for example be used in representing the earth in a two-dimensional model in the region of the poles.

FIG. 6 shows a sub-division according to an octant tree for a representation based on a three-dimensional geometrical model. Here a section 14 or a space is sub-divided into eight spatial sub-sections 15. By means of the method according to the invention, consequently here also the data of just the spatial areas are called up in a higher accuracy, at which it is required in order to obtain the desired image resolution. Here also the same number of points, for example 128×128×128 points can be called up, transmitted and centrally stored for each section, so that during sub-division of a master section 14 into eight slave sections 15 an improved spatial accuracy of the data in the region of the individual slave sections 15 results.

FIG. 7 shows a model for the use of references (so-called “hyperlinks”) on different section planes. The individual sections have references 16 to the storage point both of the data of adjacent sections and also of the data on other topics, but with the same spatial association. In this way, proceeding from the data of a section, data relating to the adjacent section or further data over the same section can be determined. In particular, the node 3 can call up the data of a section next to a section known to it without having intrinsic knowledge of the storage points of the adjacent section data. In this way the spatially distributed data call-up and storage systems may be expanded or updated at will, without the central store and evaluation units taking knowledge of the alteration during each such alteration.

FIGS. 8 to 11 show views of the earth generated by a method using a quadrant tree. The required data were called up from spatially distributed databases of research institutes.

FIG. 8 shows a view of cloud distribution on the earth surface as detected by a weather satellite. A cylindrical projection was used as a form of representation. The upper edge represents the north pole and the lower edge the south pole. A two-dimensional topographic grid network of the earth surface was selected as a representational model. As the cloud layer usually is at a distance from the earth surface, the cloud distribution was shown on a second layer located outwith the view of the earth surface. Thus there results, despite the only two-dimensional view for an observer, a possibility close to reality of approaching the earth surface “through” the cloud layer. Data generated by satellite surveillance systems of meteorological research institutes were used as data sources for the actual cloud distribution existing at the time of the imaging.

FIG. 9 shows the same cloud distribution. Now the earth has been shown as a globe, as it would appear to an observer is space. FIG. 10 shows a view of the same cloud distribution in connection with a representation of the land masses of the earth as they would appear to an observer in space. In order to show the view of the earth surface, the topographical grid network was provided with colour information from the pixel graphics of satellite images of the earth surface. As at the time of image generation actual cloud information was used for image generation, there was a view close to reality of the earth from space at the time of image generation.

FIG. 11 shows a view generated in this way of the American Caribbean coast, as it would have appeared to an observer looking north in an orbit close to the earth above the Caribbean. In addition, the actual temperature data of selected points present in tabular form were entered in display tables into the image. These temperature data were called up and transmitted through the interchange network from various meteorological research stations at various points.

Claims

1. A method of providing a pictorial representation of space-related data of a selectable object, the representation corresponding to the a view of the object by an observer with a selectable location and a selectable direction of view comprising:

(a) providing a plurality of spatially distributed data sources for storing space-related data;

(b) determining a field of view including the an area of the object to be represented through the a selection of the a distance of the observer to the object and the an angle of view of the observer to the object;

(c) requesting data for the field of view from at least one of the plurality of spatially distributed data sources;

(d) centrally storing the data for the field of view;

(e) representing the data for the field of view in a pictorial representation having one or more sections;

(f) using a computer, dividing each of the one or more sections having image resolutions below a desired image resolution into a plurality of smaller sections, requesting higher resolution space related data for each of the smaller sections from at least one of the plurality of spatially distributed data sources, centrally storing the higher resolution space related data, and representing the data for the field of view in a the pictorial representation; and

(g) repeating step (f), dividing the sections into smaller sections, until every section has the desired image resolution or no higher image resolution data is available.

2. The method of pictorial representation defined in claim 1, further including altering the selectable location and performing steps (b) through (g).

3. The method of pictorial representation defined in claim 2, further including determining the data and/or the co-ordinates of the data in terms of a new co-ordinate system.

4. The method of pictorial representation defined in claim 1, further including altering the selectable direction of the view and performing steps (b) through (g).

5. The method of pictorial representation defined in claim 4, further including determining the data and/or the co-ordinates of the data in terms of a new co-ordinate system.

6. The method of pictorial representation defined in claim 1, wherein step (f) further includes requesting data of a uniform resolution for each of the smaller sections.

7. The method of pictorial representation defined in claim 1, wherein steps (c) and (f) further include requesting data not already centrally stored from only one of the spatially distributed data sources.

8. The method of pictorial representation defined in claim 1, wherein step (f) further includes showing only the centrally stored data of each section with the highest spatial density.

9. The method of pictorial representation defined in claim 1, wherein step (f) further includes effecting the representation of the data in an optional pre-set form of representation.

10. The method of pictorial representation defined in claim 1, further including removing the data of a section from the central store when the section passes out of the field of view due to an alteration in the location or of the angle of the view.

11. The method of pictorial representation defined in claim 1, further including permanently centrally storing at least one full set of space-related data with a low spatial resolution.

12. The method of pictorial representation defined in claim 1, further including not showing the regions of the object located with respect to the observer behind non-transparent areas of the object.

13. The method of pictorial representation defined in claim 1, wherein step (f) comprises dividing each of the one or more sections using a model of the binary tree.

14. The method of pictorial representation defined in claim 1, wherein step (f) comprises dividing each of the one or more sections using a model of the quadrant tree.

15. The method of pictorial representation defined in claim 1, wherein step (f) comprises dividing the sections using a model of the octant tree.

16. The method of pictorial representation defined in claim 1, further including using an adaptive sub-division model with a plurality of models used next to one another for sub-dividing the field of view into smaller sections.

17. The method of pictorial representation defined in claim 1, wherein the data are present as pixel graphics and/or as vector graphics and/or in tabular form.

18. The method of pictorial representation defined in claim 1, wherein the object is a heavenly body.

19. The method of pictorial representation defined in claim 18, wherein steps (e) and (f) further include representating the data with a two-dimensional polygonal geometrical model of the topography of the object, the spatial relationship of the data being given by the provision of two co-ordinates on the polygonal geometrical model.

20. The method of pictorial representation defined in claim 19, wherein height information is represented as color vertices on the two-dimensional polygonal geometrical model.

21. The method of pictorial representation defined in claim 19, wherein an adaptive topographical grid model is used, the spatial distance between two grid lines becoming smaller as the topographical altitude becomes greater.

22. The method of pictorial representation defined in claim 19, wherein step (f) further includes dividing each of the one or more sections using a model of the quadrant tree.

23. The method of pictorial representation defined in claim 22, wherein step (f) further includes dividing each of the one or more sections using an adaptive sub-division model such that the sub-division merges into a binary tree at the poles.

24. The method of pictorial representation defined in claim 19, wherein in the two-dimensional polygonal grid model, spatial data are shown on a plurality of different two-dimensional layers.

25. The method of pictorial representation defined in claim 18, wherein the representation in steps (e) and (f) is in the form of a globe.

26. The method of pictorial representation defined in claim 18, wherein the representation in steps (e) and (f) is in the form of cartographic form of representation.

27. The method of pictorial representation defined in claim 1, wherein the object is the earth.

28. The method of pictorial representation defined in claim 1, wherein steps (e) and (f) further include representing the data with a polygonal grid model.

29. The method of pictorial representation defined in claim 28, wherein step (f) comprises dividing the sections using a model of the octant tree.

30. The method of pictorial representation defined in claim 1, wherein steps (e) and (f) further include representing the data with a three-dimensional geometrical model of the topography of the objects, the spatial relationship of the data being given by the provision of three co-ordinates on the geometrical model.

31. The method of pictorial representation defined in claim 1, wherein the space-related data include CAD models.

32. The method of pictorial representation defined in claim 1, further including inserting animated objects into the pictorial representation.

33. The method of pictorial representation defined in claim 1, further including inserting display tables into the pictorial representation.

34. The method of pictorial representation defined in claim 1, further including inserting information and/or directly generated image material into the representation.

35. The method of pictorial representation defined in claim 1, wherein the directly generated image material includes camera shots.

36. The method of pictorial representation defined in claim 1, wherein the space related data are provided with references to further spatial data.

37. The method of pictorial representation defined in claim 1, wherein the space related data are provided with references to thematically adjacent data.

38. The method of pictorial representation defined in claim 1, wherein the space related data are provided with references to data of the same area with another resolution.

39. The method of pictorial representation defined in claim 1 further including determining a probability for the regions surrounding the field of view that the regions will pass into the field of view when there is an alteration in the location or of the angle of view of the observer.

40. The method of pictorial representation defined in claim 39 further including requesting and centrally storing the data of the areas with the highest probability.

41. The method of pictorial representation defined in claim 1, wherein steps (c) and (f) further include transmitting data asynchronously.

42. The method of pictorial representation defined in claim 1, wherein steps (e) and (f) further include showing the data on a screen.