Method and apparatus for three-dimensional modeling via an image mosaic system

• US 20050089213A1
• Filed: 10/25/2004
• Published: 04/28/2005
• Est. Priority Date: 10/23/2003
• Status: Abandoned Application

• Current Assignee: Technest Holdings, Inc. (AccelPath, Inc.)
• Original Assignee: Technest Holdings, Inc. (AccelPath, Inc.)
• Inventors: Geng, Z. Jason
• Application Number:
  US10/973,853
• Publication Number:
  US 20050089213A1
• Time in Patent Office: Days
• US Class Current: 382/154
• CPC Class Codes: G06T 3/4038 Image mosaicing, e.g. composing plane images from plane sub-images
• CPC Class Codes: G06T 7/33 using feature-based methods
• CPC Class Codes: G06V 20/653 by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
• CPC Class Codes: G06V 2201/03 Recognition of patterns in medical or anatomical images

Abstract

An imaging method and system for 3D modeling of a 3D surface forms a mosaic from multiple uncalibrated 3D images, without relying on camera position data to merge the 3D images. The system forms the 3D model by merging two 3D images to form a mosaiced image, merging the mosaiced image with another 3D image, and repeating the merging process with new 3D images one by one until the 3D model is complete. The images are aligned in a common coordinate system via spatial transformation.

Claims

1. A method for three-dimensional (3D) modeling of a 3D surface, comprising:

obtaining a plurality of uncalibrated 3D images;

selecting a pair of 3D images out of said plurality of uncalibrated 3D images;

integrating said pair of 3D images to form a mosaiced image; and

repeating said integrating step by integrating said mosaiced image and a subsequent 3D image selected from said plurality of uncalibrated 3D images until a 3D model is completed.

2. The method of claim 1, wherein the step of integrating said pair of 3D images comprises:

filtering said pair of 3D images to remove unwanted areas of said 3D images;

aligning said pair of 3D images in a selected global coordinate system; and

merging said pair of 3D images to form said mosaiced image.

3. The method of claim 2, wherein said aligning step conducts alignment based on a surface feature that is independent from a coordinate system definition or an illumination condition.

4. The method of claim 2, wherein said merging step comprises blending a boundary between said pair of 3D images.

5. The method of claim 4, wherein said subsequent 3D image selected from said plurality of uncalibrated 3D images comprises a 3D image that overlaps said mosaiced image and covers an area of said 3D surface adjacent to an area of said 3D surface covered by said mosaiced image.

6. The method of claim 2, wherein said aligning step comprises:

selecting a first set of fiducial points on a first of said pair of 3D images;

selecting a second set of fiducial points on a second of said pair of 3D images, wherein said first and second sets of fiducial points correspond to overlapping portions of said pair of 3D images; and

aligning corresponding fiducial points between said first and second sets of fiducial points to join said pair of 3D images to form said mosaiced image.

7. The method of claim 6, wherein said step of aligning the corresponding fiducial points comprises deriving a spatial transformation matrix via a least squares minimization method to align the pair of 3D images into a common coordinate system.

8. The method of claim 4, wherein said blending comprises:

determining a boundary area between overlapping portions of said pair of 3D images;

smoothing said boundary area using a fuzzy weighting averaging function; and

conducting a re-sampling operation by sampling a plurality of points on the 3D surface and calculating 3D coordinates using an interpolation algorithm on the sampled points.

9. The method of claim 1, further comprising compressing said 3D model via an image compression process.

10. The method of claim 9, wherein said compressing conducts compression via a multi-resolution triangulation algorithm, which includes the steps of:

expressing the 3D model as 3D polygons;

converting the 3D polygons from the expressing step into 3D triangles;

iteratively removing triangulation vertices from the 3D triangles to generate a reduced 3D model; and

calculating a 3D distance between the 3D model and the reduced 3D model.

11. The method of claim 1, further comprising the step of overlaying a two-dimensional (2D) texture/color overlay over the 3D model.

12. An apparatus for three-dimensional (3D) modeling of a 3D surface, comprising:

an optical device configured to obtain a plurality of uncalibrated 3D images that include data corresponding to a distance between a focal point of the optical device and a point on the 3D surface; and

a processor coupled to the optical device that includes;

a selector that selects a pair of 3D images out of said plurality of uncalibrated 3D images obtained by said optical device; and

an integrator configured to integrate said pair of 3D images to form a mosaiced image,

wherein said integrator repeats said integration process by integrating the mosaiced image and a subsequent 3D image selected from said plurality of uncalibrated 3D images until a 3D model is completed.

13. The apparatus of claim 12, wherein the processor further includes a filter configured to remove undesired areas of said 3D images before the integrator integrates the 3D images.

14. The apparatus of claim 12, wherein the integrator integrates the 3D images by aligning the pair of 3D images in a selected global coordinate system based on a surface feature that is independent from a coordinate system definition and merges the pair of 3D images to form the mosaiced image.

15. The apparatus of claim 12, wherein said integrator is configured to integrate said 3D images by:

selecting a first set of fiducial points on a first of said pair of 3D images;

selecting a second set of fiducial points on said second of said pair of 3D images, wherein said first and second sets of fiducial points correspond to overlapping portions of said pair of 3D images; and

aligning corresponding fiducial points between said first and second sets of fiducial points to join the pair of 3D images to form the mosaiced image.

16. The apparatus of claim 15, wherein the integrator aligns the corresponding fiducial points by deriving a spatial transformation matrix via a least square minimization method to align the pair of 3D images into a common coordinate system.

17. The apparatus of claim 15, wherein the integrator blends a boundary between 3D images by:

determining a boundary area between overlapping portions of the pair of 3D images;

smoothing the boundary area using a fuzzy weighting averaging function; and

conducting a re-sampling operation by sampling a plurality of points on the 3D surface and calculating 3D coordinates using an interpolation algorithm on the sampled points.

18. The apparatus of claim 12, wherein the processor further comprises a compressor configured to compresses data corresponding to the 3D model.

19. The apparatus of claim 18, wherein said compressor is configured to conduct compression via a multi-resolution triangulation algorithm by:

expressing the 3D model as 3D polygons;

converting the 3D polygons into 3D triangles;

iteratively removing triangulation vertices from the 3D triangles to generate a reduced 3D model; and

calculating a 3D distance between the 3D model and the reduced 3D model.

20. The apparatus of claim 12, further comprising an overlay mechanism configured to overlay said 3D model with a two-dimensional (2D) texture/color overlay.

21. An automated computer process for generating a mosaic of a 3D object from a plurality of uncalibrated 3D images comprising the steps of:

capturing a plurality of 3D data images of surfaces of an object or scene from a number of viewpoints;

automatically aligning said plurality of 3D data images into a selected coordinate system based on parameters of a 3D camera utilized to capture said 3D data images; and

merging said plurality of aligned 3D data images into a single 3D geometric model.

22. The computer process of claim 21 wherein said automatically aligning comprises a step of aligning 3D image planes each plane including thousands of 3D points to facilitate a closest point search on a first of said planes with a selectable point on a second of said image planes.

23. The computer process of claim 22 wherein the alignment step comprises a pinhole mathematical matrix step to convert a 2D closest point on a selected one of planes with a 3D point on another selected data plane.

24. The computer process of claim 23 wherein said pinhole mathematical matrix step comprises converting a 2D closest point search on a selected one of said 3D image planes into a 1D point search wherein a point P may be mathematically expressed as:

$s<br><br>\left(\begin{array}{c}u\\ v\\ 1\end{array}\right)=P<br><br>\left(\begin{array}{c}x\\ y\\ z\\ 1\end{array}\right)$

wherein s is an arbitrary scale factor and P is a perspective projection matrix.

25. The computer process of claim 24 wherein for said pinhole mathematical camera model, the value of P may be mathematically expressed as:

P=A[R,T]

where A is a matrix to map a normalized image coordinate to a retinal image coordinates of a 3D camera and (R,T) is a 3DM matrix for translating relative and translation values for a generalized world coordinate system to the recording camera coordinate system.

26. The computer process of claim 21 wherein said automatic aligning is based upon mathematical matrix utilizing constants of a 3D camera configured to capture said 3D images.

27. The computer process of claim 26 further comprising calibrating said 3D camera to derive at least a plurality of constants to be used in a pinhole mathematical camera model.

28. The computer process of claim 27 wherein said step of calibrating said 3D camera further comprises determining a group of physical characteristics of said 3D camera including coordinates of said camera intersection of optical axis and image plane.

29. A computer modeling apparatus for generating a 3D mosaic from a plurality of uncalibrated 3D surface images comprising:

a 3D camera; and

a 3D modeling computer processor for merging said 3D surface images into a single 3D geometric model

wherein said 3D modeling computer processor is configured to execute a plurality of 3D data surface images to search a plurality of uncalibrated images, to facilitate a data point search to identify and locate closest data points on selected ones of said 3D surface images, and to facilitate alignment of said uncalibrated 3D surface images.

30. The 3D computer modeling apparatus of claim 29 further comprising a computer aligning processor configured to align said plurality of uncalibrated 3D images into a selected coordinate system.