Three-dimensional imaging system

• US 10,182,223 B2
• Filed: 11/19/2010
• Issued: 01/15/2019
• Est. Priority Date: 09/03/2010
• Status: Active Grant

• Current Assignee: California Institute of Technology
• Original Assignee: California Institute of Technology
• Inventors: Gharib, Morteza, Harvard, Alexei, Hsieh, Scott, Lu, Jian
• Primary Examiner(s): Sun, Yulin
• Application Number:
  US13/820,116
• Publication Number:
  US 20130235165A1
• Time in Patent Office: 2,979 Days
• Field of Search: 348 50
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/30036 Dental; Teeth
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 7/579 from motion
• CPC Class Codes: G06T 7/593 from stereo images
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: H04N 13/207 using a single 2D image sensor
• CPC Class Codes: H04N 13/214 using spectral multiplexing
• CPC Class Codes: H04N 13/25 using two or more image sensors with different characteristics other than in their location or field of view, e.g. having different resolutions or colour pickup characteristics; using image signals from one sensor to control the characteristics of another sensor
• CPC Class Codes: H04N 13/257 Colour aspects

Abstract

Hardware and software configurations, optionally, for performing profilometry of an object are disclosed. An advantageous imaging device is described. An advantageous approach to determining imager position is also described. Each aspect described may be used independently of the other. Moreover, the teaching may find use in other fields including velocimetry, etc.

Claims

1. A method of determining camera position for scanner output with scanned image frames of an object, the image frames representing three dimensional dense data sets, the method comprising:

determining a first, tentative camera position from a plurality of image frames taken after one another in time,

determining a second, rough camera position by performing dense information set matching between two image frames in positions capable of being matched as provided by the tentative camera position,

after determining the second, rough camera position, then making a first aggregation of the three dimensional dense data sets using the second, rough camera position determination, wherein the first, tentative camera position is not used in making the first aggregation, and

processing point collections from the plurality of image frames with defocusing equations to produce three dimensional data.

2. The method of claim 1, wherein the first, tentative camera position is determined by performing dense information set matching.

3. The method of claim 2, in which the three-dimensional data sets have associated three-dimensional keypoint data sets, wherein:

in instances where the dense information set matching is not accomplished to establish the first, tentative camera position information, it is determined by matching frames based their keypoint data sets.

4. The method of claim 1, wherein the first aggregation of the dense data sets is used for display.

5. The method of claim 1, wherein the first, tentative camera position and the second, rough camera position are determined in real time on a computer processor.

6. The method of claim 1 further comprising:

determining a third, refined camera position using the second, rough camera position.

7. The method of claim 6, wherein the third, refined camera position is determined through post-processing.

8. The method of claim 6, wherein determining the third, refined camera position comprises:

matching a plurality of the three-dimensional dense data sets at a first threshold distance;

matching another plurality of three-dimensional dense data sets to one of the plurality matched at the first distance,

matching another plurality of three-dimensional dense data sets to another one of the plurality matched at the first level until at least substantially all frames of interest are so-matched; and

determining the relative position of the matched sets.

9. The method of claim 8, further comprising:

producing computer readable scan output for producing a physical model from a second aggregation of the dense data sets using the third, refined camera position.

10. The method of claim 1, wherein processing point collections from the plurality of image frames with defocusing equations to produce three dimensional data comprises processing red and blue channel point collections.

11. The method of claim 1, further comprising referencing a calibration table, formed by imaging a known pattern, to account for nonlinearities for the point collections.

12. The method of claim 11, wherein the known pattern is a grid pattern.