GPS-enhanced system and method for automatically capturing and co-registering virtual models of a site

Abstract

A system for capturing a virtual model of a site includes a range scanner for scanning the site to generate range data indicating distances from the range scanner to real-world objects. The system also includes a global positioning system (gps) receiver coupled to the range scanner for acquiring gps data for the range scanner at a scanning location. In addition, the system includes a communication interface for outputting a virtual model comprising the range data and the gps data.

Description

CROSS REFERENCE TO RELATED APPLICATIONS

Y=R sin φ  Eq. 2
Z=R cos φsin θ  Eq. 3
In certain embodiments, the geometry of the range scanner 102 (e.g., the axis of rotation, offset, etc.) may result in a polar-like coordinate system that requires different transformations, as will be known to those of skill in the art. In general, the origin of each of the scanning coordinate systems 402a-c is the light-reception point of the lidar 103.

Referring to FIG. 6, in order to combine or “co-register” the virtual models 234 from the various scanning positions, the transformation module 229 transforms the range data 302a-c from their respective scanning coordinate systems 402a-c to a single modeling coordinate system 602 that is independent of the scanning positions and the orientation of the range scanner 102.

In one embodiment, the modeling coordinate system 602 is based on a geographic coordinate system, such as Universal Transverse Mercator (UTM), Earth-Centered/Earth-Fixed (ECEF), or longitude/latitude/altitude (LLA). GPS receivers 104 are typically able to display Earth-location information in one or more of these coordinate systems. UTM is used in the following examples because it provides convenient Cartesian coordinates in meters. In the following examples, the UTM zone is not shown since the range data 302 will typically be located within a single zone.

As depicted in FIG. 6, the transformation module 229 initially rotates each set of range data 302a-c by the bearing of the range scanner 102 obtained from the orientation information 305. After a set of range data 302 has been converted into Cartesian coordinates, each point may be rotated around the origin by the following transformation, where b is the bearing.
X₁=X cos (b)−Z sin (b)   Eq. 4
Z₁=Z cos (b)+X sin (b)   Eq. 5
These equations assume that the range scanner 102 was level at the time of scanning, such that the XZ planes of the scanning coordinate system 402 and modeling coordinate system 602 are essentially co-planer. If, however, the range scanner 102 was tilted with respect to the X and/or Z axes, the transformations could be modified by one of skill in the art.

Next, as shown in FIG. 7, the transformation module 229 uses the GPS data 304 to translate the range data 302 to the correct location within the modeling coordinate system 602. In one embodiment, this is done by adding the coordinates from the GPS data 304 to each of the range data coordinates, as shown below.
X₂=X₁+GPS_E   Eq. 6
Y₂=Y₁+GPS_H   Eq. 7
Z₂=Z₁+GPS_N   Eq. 8
where

• • GPS_E is the UTM “easting,”
  • GPS_H is the altitude (typically the height above the reference ellipsoid), and
  • GPS_N is the UTM “northing.”
    The UTM easting and northing for a number of points in the modeling coordinate system 602 are shown in FIG. 7, and are typically represented on maps using the “mE” (meters East) and “mN” (meters North) labels.

Those of skill in the art will recognize that the invention is not limited to UTM coordinates and that transformations exist for other coordinate systems, such as ECEF and LLA. In certain embodiments, the modeling coordinate system 602 may actually be referenced to a local landmark or a point closer to the range data 302, but will still be geographically oriented.

In the preceding example, the units of the range data 302 and GPS data 304 are both in meters. For embodiments in which the units differ, a scaling transformation will be needed. Furthermore, while FIGS. 6 and 7 show particular types of transformations, those of skill in the art will recognize that different transformations may be required based on the geometry of the range scanner 102, whether the range scanner 102 was tilted with respect to the XZ plane, and the like.

When the transformation is complete, the co-registration module 228 co-registers or combine combines the range data 302a-c from the various views into a co-registered model 702 of the entire site 104. This may involve, for example, combining the sets of range data 302a-c into a single data structure, while still preserving the ability to access the individual sets.

In one embodiment, the co-registered model 702 includes GPS data 304 for at least one point. This allows the origin of the modeling coordinate system 602 to be changed to any convenient location, while still preserving a geographic reference.

As illustrated in FIG. 7, a co-registered model 702 is not perfect. Noise and other sources of error may result in various gaps, incongruities, regions of overlap, etc. Thus, while the co-registration module 228 automatically places the range data 302a-c within close proximity to their expected locations, eliminating the need for human decision-making, the range data 302a—c are not truly merged. For example, two separate points may exist within the co-registered model 702 that should actually refer to the same physical location in the site 104.

Referring to FIG. 8, a merging module 230 addresses this problem by merging the range data 302a-c from the co-registered model 702 into a single merged model 802. The merging module 230 makes fine adjustments to the transformed range data 302a—c, eliminating the gaps, incongruities, and regions of overlap. In addition, the merging module 230 may eliminate redundancy by merging points from the transformed range data 302a that represent the same physical location. This is accomplished, in one embodiment, using an iterative closest point (ICP) algorithm, as known to those of skill in the art.

In one embodiment, the merging module 230 incorporates the Scanalyze™ product available from Stanford University. Scanalyze™ is an interactive computer graphics application for viewing, editing, aligning, and merging range images to produce dense polygon meshes.

Scanalyze™ processes three kinds of files: triangle-mesh PLY files (extension .ply), range-grid PLY files (also with extension .ply), and SD files (extension .sd). Triangle-mesh PLY files encode general triangle meshes as lists of arbitrarily connected 3D vertices, whereas range-grid PLY files and SD files encode range images as rectangular arrays of points. SD files also contain metadata that describe the geometry of the range scanner 102 used to acquire the data. This geometry is used by Scanalyze™ to derive line-of-sight information for various algorithms. PLY files may also encode range images (in polygon mesh form), but they do not include metadata about the range scanner and thus do not provide line-of-sight information.

Once the PLY or SD files have been loaded, they can be pairwise aligned using a variety of techniques—some manual (i.e. pointing and clicking) and some automatic (using a variant of the ICP algorithm).

Pairs of scans can be selected for alignment either automatically (so-called all-pairs alignment) or manually, by choosing two scans from a list. These pairwise alignments can optionally be followed by a global registration step whose purpose is to spread the alignment error evenly across the available pairs. The new positions and orientations of each PLY or SD file can be stored as a transform file (extension .xf) containing a 4×4 matrix.

Referring to FIG. 9, the visualization module 232 uses the merged model 802 of FIG. 8 to create an interactive, three-dimensional visualization 112 of the site 104. To accomplish this, the visualization module 232 may convert the transformed/merged range data 302 into a polygon mesh 902. Various known software applications are capable of producing a polygon mesh 902 from range data 302, such as the Volumetric Range Image Processing Package (VripPack), available from Stanford University. VripPack is a set of source code, scripts, and binaries for creating surface reconstructions from range images. For example, the VripPack merges range images into a compressed volumetric grid, extracts a surface from the compressed volumetric grid, fills holes in the reconstruction by carving out empty space, removes small triangles from the reconstruction, and performs a simple 4-level decimation for interactive rendering.

The visualization module 232 also decomposes the digital images 306 into textures 904, which are then applied to the polygon mesh 902. In essence, the digital images 306 are “draped” upon the polygon mesh 902. Due to the relatively higher resolution of the digital images 306, the textures 904 add a high degree of realism to the visualization 112. Techniques and code for applying textures 904 to polygon meshes 902 are known to those of skill in the art.

In one embodiment, the mesh 902 and textures 904 are used to create the visualization 112 of the site 104 using a standard modeling representation, such as the virtual reality modeling language (VRML). Thereafter, the visualization 112 can be viewed using a standard VRML browser, or a browser equipped with a VRML plugin, such as the Microsoft™ VRML Viewer. Of course, the visualization 112 could also be created using a proprietary representation and viewed using a proprietary viewer.

As depicted in FIG. 9, the browser may provide navigation controls 906 to allow the user to “walk through” the visualization 112. In addition, the user may delete or move objects shown in the visualization 112 or modify the visualization 112 in other ways. As noted, such visualization 112 are highly beneficial in the fields of architecture, landscape design, land use, erosion control, and the like.

FIG. 10 is a flowchart of a method 1000 for capturing and co-registering virtual models 234 of a site 104. Initially, the site 104 is scanned 1002 to generate a first set of range data 302 indicating distances from a range scanner 102 at a first location to real-world objects in the site 104. A GPS receiver then acquires 1004 GPS data 304 relative to the range scanner 102 at the first location, after which the range scanner 102 outputs 1006 a first virtual model 234 comprising the first sets of range data 302 and GPS data 304.

After then range scanner 102 is moved to a second location, the method 1000 continues by scanning 1008 the site 104 to generate a second set of range data 302 indicating distances from the range scanner 102 at the second location to real-world objects in the site 104. In addition, the GPS receiver 116 acquires 1010 a second set of GPS data 304 relative to the range scanner 102 at the second location, after which the range scanner 102 outputs 1012 a second virtual model 234 comprising the second sets of range data 302 and GPS data 304.

In one configuration, a transformation module 229 then uses 1014 the sets of GPS data 304 to transform the sets of range data 302 from scanning coordinate systems 402 to a single modeling coordinate system 602. Thereafter, the transformed range data 302 can be merged and visualized using standard applications.

As illustrated in FIG. 11, a range scanner 102 may be used to scan multiple sites 104a-b within a particular area 1102 to create multiple site models 1104a-b using the techniques discussed above. The sites 104a-b may or may not be contiguous, although they are typically in close proximity or related in some manner. For instance, the area 1102 may represents represent a town, campus, golf course, etc., while the sites 104a-b may correspond to different buildings or structures.

The site models 1104a-b may be co-registered models 702 or merged models 802, as previously shown and described. Furthermore, as previously noted, a site model 1104a-b may include GPS data 304.

In one embodiment, the transformation module 229 uses the sets of GPS data 304a-b to combine the individual site models 1104a-b into a single area model 1106. This may be done in the same manner as the virtual models 302a-c of FIG. 6 were transformed and combined into the co-registered model 702. Specifically, the GPS data 304 provides a common reference point for each site model 1104a-b, allowing the co-registration and/or transformation modules 228, 229 to make any necessary transformations.

The resulting area model 1106 may then be used to produce an interactive, three-dimensional visualization 112 of the entire area 1102 that may be used for many purposes. For example, a user may navigate from one site 104 to another within the area 1102. Also, when needed, a user may remove any of the site models 1104 from the area model 1106 to visualize the area 1102 within the objects from the removed site model 1104. This may be helpful in the context of architectural or land-use planning.

While specific embodiments and applications of the present invention have been illustrated and described, it is to be understood that the invention is not limited to the precise configuration and components disclosed herein. Various modifications, changes, and variations apparent to those skilled in the art may be made in the arrangement, operation, and details of the methods and systems of the present invention disclosed herein without departing from the spirit and scope of the invention.

Claims

1. A system for capturing a virtual model of a site including one or more occluded surfaces when viewed from any given perspective, the system comprising:

a range scanner for automatically scanning a site from a plurality of different fixed locations to generate a separate set of range data at each scanning location indicating distances from the range scanner to real-world objects within the site, each set of range data comprising a three-dimensional model of the same site from a different perspective, wherein at least one set of range data includes a surface of a real-world object that is occluded in at least one other set of range data;

a digital camera coupled to the range scanner for obtaining digital images of the real-world objects scanned by the range scanner at each location;

a global positioning system (gps) receiver coupled to the range scanner for acquiring gps data for the range scanner at a each scanning location, wherein the gps receiver interacts with a separate base station to achieve sub-meter accuracy;

an orientation indicator coupled to the range scanner for indicating an orientation of the range scanner at each scanner location;

a transformation module for using the gps data with orientation data information for the range scanner at each scanning location to automatically transform the sets of range data from individual scanning coordinate systems based on the scanning locations to a single modeling coordinate system; and

a co-registration module for automatically co-registering the transformed sets of range data into a single virtual model of the site that includes the one or more occluded surfaces.

2. The system of claim 1, further comprising:

a visualization module for converting the co-registered virtual model of the site into a polygon mesh and for applying textures to the polygon mesh derived from the digital imagery to create an a visualization of the site that is substantially free of occlusions, the textures being derived from the digital images.

3. The system of claim 1, further comprising:

a merging module for merging at least two points represented within the co-registered virtual model that correspond to the same physical location within the site.

4. The system of claim 1, wherein the modeling coordinate system is a geographic coordinate system.

5. The system of claim 2, wherein the orientation indicator comprises a bearing indicator for indicating the bearing of the range scanner.

6. The system of claim 1, wherein the gps data is selected from the group consisting of longitude, latitude, altitude, Universal Transverse Mercator (UTM) coordinates, and Earth-Centered/Earth-Fixed (ECEF) coordinates.

7. The system of claim 1, wherein at least two of the sets of range data indicate a distance from the range scanner to the same physical location within the site.

8. The system of claim 1, wherein the virtual model associates the digital images of the real-world objects with the corresponding range data.

9. The system of claim 1, wherein the range scanner comprises:

a servo for continuously changing an orientation of the range scanner with respect to a fixed location to scan the site; and

a lidar to obtain range measurements to real-world objects along a changing path of the range scanner responsive to the servo.

10. A system for capturing a virtual model of a site including one or more occluded surfaces when viewed from any given perspective, the system comprising:

a range scanner for automatically scanning the site to generate a first set of range data indicating distances from the range scanner at a first location to real-world objects in the site, wherein the range scanner is to automatically re-scan the site to generate a second set of range data indicating distances from the range scanner at a second scanning location to real-world objects in the site, each set of range data comprising a three-dimensional model of the same site from a different perspective, wherein the second set of range data includes a surface of a real-world object that is occluded in the first set of range data;

a digital camera coupled to the range scanner for obtaining digital images of the real-world objects scanned by the range scanner at each location;

a global positioning system (gps) receiver coupled to the range scanner for acquiring a first set of gps data for the range scanner at the first scanning location and a second set of gps data for the range scanner at the second location, wherein the gps receiver interacts with a separate base station to achieve sub-meter accuracy;

an orientation indicator for indicating an orientation of the range scanner at each scanning location;

a transformation module for using the first and second sets of gps data with orientation data information for the range scanner at the scanning locations to automatically transform the first and second sets of range data from local coordinate systems referenced to the scanning locations to a single coordinate system independent of the scanning locations;

a co-registration module for automatically co-registering the first and second sets of range data into a single virtual model of the site that includes the one or more occluded surfaces; and

a merging module for merging at least two points represented within the co-registered virtual model that correspond to the same physical location within the site.

11. The system of claim 10, further comprising:

a visualization module for converting the co-registered virtual model of the site into a polygon mesh and for applying textures to the polygon mesh derived from the digital imagery to create an a visualization of the site that is substantially free of occlusions, the textures being derived from the digital images.

12. A system for modeling an object including one or more occluded surfaces when viewed from any vantage point, the system comprising:

a range scanner for automatically scanning an object from a plurality of fixed vantage points to generate a plurality of separate range images, each range image comprising a three-dimensional model of the object from a different perspective, wherein at least one range image includes a surface of the object that is occluded in at least one other range image;

a digital camera coupled to the range scanner for obtaining digital images of the object from each vantage point;

a global positioning system (gps) receiver for obtaining gps readings for the range scanner at each vantage point, wherein the gps receiver interacts with a separate base station to achieve sub-meter accuracy;

an a bearing indicator coupled to the range scanner for indicating a bearing of the range scanner at each scanning location;

a transformation module for using the gps readings associated with each range image, as well as information about the range scanner's bearing at each vantage point, to automatically transform the range images from local coordinate systems relative to the vantage points to a single coordinate system independent of the vantage points; and

a co-registration module for automatically co-registering the transformed range images into a single virtual model of the object that includes the one or more occluded surfaces.

13. The system of claim 12, further comprising:

a visualization module for converting the co-registered virtual model of the object into a polygon mesh and for applying textures to the polygon mesh derived from the digital imagery to create an a visualization of the object that is substantially free of occlusions, the textures being derived from the digital images.

14. The system of claim 12, wherein

the range scanner comprises

a servo for continuously changing an orientation of the range scanner with respect to a fixed location to scan the object; and

a lidar to obtain range measurements of the object along a changing path of the range scanner responsive to the servo.

15. The system of claim 12, wherein the virtual model is to associate the digital imagery images and the corresponding range images within the virtual model.

16. The system of claim 12, further comprising:

a merging module for merging at least two points represented within the co-registered range images that correspond to the same physical location on the object.

17. A method for capturing a virtual model of a site including one or more occluded surfaces when viewed from any given perspective, the method comprising:

automatically scanning a site from a plurality of different fixed locations to generate a separate set of range data at each scanning location indicating distances from a range scanner to real-world objects within the site, each set of range data comprising a three-dimensional model of the same site from a different perspective, wherein at least one set of range data includes a surface of a real-world object that is occluded in at least one other set of range data;

obtaining digital images of the real-world objects scanned by the range scanner at each location;

acquiring global positioning system (gps) data for the range scanner at each scanning location using a gps receiver that interacts with a separate base station to achieve sub-meter accuracy;

obtaining orientation data information for the scanner at each scanning location;

automatically transforming the separate sets of range data from individual scanning coordinate systems to a modeling coordinate system using the gps data with the orientation data information for the range scanner at each scanning location; and

automatically co-registering the transformed sets of range data into a single virtual model of the site that includes the one or more occluded surfaces.

18. The method of claim 17, further comprising:

converting the co-registered virtual model of the site into a polygon mesh; and

applying textures to the polygon mesh derived from the digital imagery to create an a visualization of the site that is substantially free of occlusions, the textures being derived from the digital images.

19. The method of claim 17, further comprising:

merging at least two points represented within the co-registered virtual model that correspond to the same physical location within the site.

20. The method of claim 17, wherein the modeling coordinate system is a geographic coordinate system.

21. The method of claim 17, wherein the orientation information includes a bearing of the range scanner, the method further comprising:

determining the bearing of the range scanner.

22. The system method of claim 17, wherein the gps data is selected from the group consisting of longitude, latitude, altitude, Universal Transverse Mercator (UTM) coordinates, and Earth-Centered/Earth-Fixed (ECEF) coordinates.

23. The method of claim 17, wherein at least two of the sets of range data indicate a distance from the range scanner to the same physical location within the site.

24. The method of claim 17, further comprising:

associating the digital images of the real-world objects with the corresponding range data.

25. The method of claim 17, wherein scanning comprises:

continuously changing an orientation of the range scanner with respect to a fixed location to scan the site; and

obtaining range measurements to real-world objects along a changing path of the range scanner.

26. A method for capturing a virtual model of a site including one or more occluded surfaces when viewed from any given perspective, the method comprising:

automatically scanning the site to generate a first set of range data indicating distances from a range scanner at a first location to real-world objects in the site, wherein the first set of range data comprises a three-dimensional model of the site from a first perspective;

obtaining digital images of the real-world objects scanned by the range scanner at the first location;

acquiring a first set of global positioning system (gps) data for the range scanner at the first location using a gps receiver that interacts with a base station to achieve sub-meter accuracy;

determining orientation information for the range scanner at the first location;

scanning the same site from a second perspective to generate a second set of range data indicating distances from the range scanner at a second location to real-world objects in the site, wherein the second set of range data comprises a three-dimensional model of the site from a second perspective, wherein the second set of range data includes a surface of a real-world object that is occluded in the first set of range data;

obtaining digital images of the real-world objects scanned by the range scanner at the second location;

acquiring a second set of gps data for the range scanner at the second location;

determining orientation information for the range scanner at the second location;

automatically transforming the first and second sets of range data from individual local coordinate systems to a single coordinate system independent of the range scanner locations using the first and second sets of gps data with the orientation information;

automatically co-registering the first and second sets of range data into a single virtual model of the site that includes the one or more occluded surfaces;

converting the co-registered virtual model of the site into a polygon mesh; and

applying textures to the polygon mesh derived from the digital imagery to create an a visualization of the site that is substantially free of occlusions, the textures being derived from the digital images.

27. A method for modeling an object including one or more occluded surfaces when viewed from any vantage point, the method comprising:

automatically scanning an object from a plurality of fixed vantage points to generate a plurality of separate range images, each range image comprising a three-dimensional model of the object from a different perspective, wherein at least one range image includes a surface of the object that is occluded in at least one other range image;

obtaining digital images of the object from each vantage point;

obtaining a bearing of the scanner at each vantage point;

acquiring global position system (gps) readings for the range scanner at each vantage point using a gps receiver that accesses a separate base station to achieve sub-meter accuracy;

transforming the range images from local coordinate systems relative to the vantage points to a single coordinate system independent of the vantage points using the gps readings associated with each range image, as well as information about the range scanner's bearing at each vantage point; and

automatically co-registering the transformed range images into a single virtual model of the object that includes the one or more occluded surfaces.

28. The method of claim, 27, further comprising:

converting the co-registered virtual model of the object into a polygon mesh; and

applying textures to the polygon mesh derived from the digital imagery to create an a visualization of the object that is substantially free of occlusions, the textures being derived from the digital images.

29. The system method of claim 27, wherein scanning comprises:

continuously changing an orientation of the range scanner with respect to a fixed location to scan the object; and

obtaining range measurements of the object along a changing path of the range scanner responsive to the servo.

30. The system method of claim 27, wherein the gps data is selected from the group consisting of longitude, latitude, uniform, altitude, Universal Transverse Mercator (UTM) coordinates, and Earth-Centered/Earth-Fixed (ECEF) coordinates.

31. The method of claim 27, further comprising:

associating the digital imagery images with the corresponding range images within the virtual model.

32. The method of claim 27,

wherein at least two of the range images depict the same physical location within the site.

33. The system of claim 27, wherein the gps data is selected from the group consisting of longitude, latitude, altitude, Universal Transverse Mercator (UTM) coordinates, and Earth-Centered/Earth-Fixed (ECEF) coordinates.

34. The system method of claim 27,

wherein at least two of the range images depict the same physical location on the object.

35. An apparatus for capturing a virtual model of a site including one or more occluded surfaces when viewed from any given perspective, the system apparatus comprising:

scanning means for automatically scanning a site from a plurality of different fixed locations to generate a separate set of range data at each scanning location indicating distances from the scanning means to real-world objects within the site, each set of range data comprising a three-dimensional model of the same site from a different perspective, wherein at least one set of range data includes a surface of a real-world object that is occluded in at least one other set of range data;

camera means coupled to the scanning means for obtaining digital images of the real-world objects scanned by the scanning means at each location;

position detection means coupled to the scanning means for acquiring global positioning system (gps) data for the scanning means at a each scanning location, wherein the position detection means interacts with a separate base station to achieve sub-meter accuracy;

an orientation detection means coupled to the scanning means for indicating an orientation of the scanning means at each scanning location;

transformation means for using the gps data with orientation data information for the scanning means at each scanning location to automatically transform the sets of range data from individual scanning coordinate systems based on the scanning locations to a single modeling coordinate system; and

co-registration means for automatically co-registering the transformed sets of range data into a single virtual model of the site that includes the one or more occluded surfaces.

36. A computer program product comprising program code for performing a method for capturing a virtual model of a site including one or more occluded surfaces when viewed from any given perspective, the computer program product comprising:

program code for automatically scanning a site from a plurality of different fixed locations to generate a separate set of range data at each scanning location indicating distances from a range scanner to real-world objects within the site, each set of range data comprising a three-dimensional model of the same site from a different perspective, wherein at least one set of range data includes a surface of a real-world object that is occluded in at least one other set of range data;

program code for obtaining digital images of the real-world objects scanned by the range scanner at each location;

program code for acquiring global positioning system (gps) data for the range scanner at each scanning location using a gps receiver that interacts with a separate base station to achieve sub-meter accuracy;

program code for obtaining orientation data information for the scanner at each scanning location;

program code for automatically transforming the separate sets of range data from individual scanning coordinate systems to a modeling coordinate system using the gps data with the orientation data information for the range scanner at each scanning location; and

program code for automatically co-registering the transformed sets of range data into a single virtual model of the site that includes the one or more occluded surfaces.

37. The system of claim 1, wherein the gps receiver achieves sub-centimeter accuracy.

38. The system of claim 1, wherein the orientation indicator comprises a compass capable of digital output.

39. The system of claim 1, wherein the orientation indicator comprises at least two gps readings to indicate the orientation of the range scanner at each location.

40. The system of claim 1, further comprising a second digital camera for obtaining digital images of the real-world objects scanned by the range scanner at each location, wherein the digital camera and the second digital camera are set to focus in a stereo vision arrangement.

41. The method of claim 17, wherein the gps receiver achieves sub-centimeter accuracy.

42. The method of claim 17, wherein the orientation information comprises data from a compass capable of digital output.

43. The method of claim 17, wherein the orientation information comprises at least two gps readings to indicate an orientation of the range scanner at each location.

44. The method of claim 17, further comprising obtaining digital images of the real-world objects scanned by the range scanner at each location using a second digital camera, wherein the digital camera and the second digital camera are set to focus in a stereo vision arrangement.