Method and system for obtaining high resolution 3-D images of moving objects by use of sensor fusion

• US 20070064242A1
• Filed: 09/01/2005
• Published: 03/22/2007
• Est. Priority Date: 09/01/2005
• Status: Active Grant

• Current Assignee: James R Glidewell Dental Ceramics Incorporated
• Original Assignee: Sonaray, Inc.
• Inventors: Childers, Edwin
• Granted Patent: US 7,672,504 B2
• Time in Patent Office: Days
• US Class Current: 356/601
• CPC Class Codes: G01B 11/24 for measuring contours or curvatures
• CPC Class Codes: G01S 17/48 Active triangulation systems, i.e. using the transmission and reflection of electromagnetic waves other than radio waves
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 17/89 for mapping or imaging
• CPC Class Codes: G01S 7/481 Constructional features, e.g. arrangements of optical elements
• CPC Class Codes: G01S 7/4817 relating to scanning
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 2207/30008 Bone
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light

Abstract

A system to scan 3D images applies sensor fusion of a passive triangulation sensor in combination with an active triangulation sensor to obtain high resolution 3D surface models from objects undergoing arbitrary motion during the data acquisition time.

Claims

1. A scanner, comprising:

A passive triangulation sensor; and

an active triangulation sensor coupled to the passive triangulation sensor to obtain a high resolution 3D surface model from an object undergoing arbitrary motion during image acquisition.

2. The scanner of claim 1, wherein the passive triangulation sensor comprises a full field passive sensor that captures images of a sparse set of arbitrarily distributed fiducials on the surface of the object.

3. The scanner of claim 1, wherein the active sensor projects a pattern bisecting the object.

4. The scanner of claim 3, wherein the pattern comprises one of:

a point, a line, a 2D pattern.

5. The scanner of claim 1, wherein the sensors scan at frame rates between approximately 2 and 1000 frames per second.

6. The scanner of claim 1, wherein the active sensor and the passive sensor operate at approximately the same frame rate or in approximate synchronicity with one another.

7. The scanner of claim 1, wherein the sensors are mounted on a fixed or mobile platform.

8. The scanner of claim 1, comprising a plurality of fiducials distributed on the object to determine per frame coordinate transformations to accommodate for between frame motion and to align the active triangulation sensor surface range data information with a coordinate reference frame that is fixed with respect to the surface of the object.

9. The scanner of claim 8, wherein the fiducials comprise a sparse distribution with less than 10,000 fiducials per square millimeter.

10. The scanner of claim 8, wherein images of the fiducials are processed using an ego-motion computation technique.

11. A method for forming 3-D surface models of an object with arbitrary motion relative to an imaging system, comprising:

capturing images of an object having a sparse set of arbitrarily distributed fiducials on its surface with a passive triangulation sensor;

acquiring surface range data using an active triangulation sensor in synchronicity with the passive triangulation sensor; and

using frame-to-frame relative movement of the imaged fiducials from the passive triangulation sensor to determine a coordinate transformation that aligns the active triangulation sensor surface range data with a coordinate reference frame fixed to the object.

12. The method of claim 11, wherein the passive triangulation sensor comprises a full field passive sensor that captures images of a sparse set of arbitrarily distributed fiducials.

13. The method of claim 11, wherein the active sensor projects a pattern bisecting the object.

14. The method of claim 13, wherein the pattern comprises one of:

a point, a line, a 2D pattern.

15. The method of claim 11, wherein the sensors scan at frame rates approximately between 2 and 1000 frames per second.

16. The method of claim 11, wherein the active sensor and the passive sensor operate at approximately the same frame rate or in approximate synchronicity with one another.

17. The method of claim 11, wherein the sensors are mounted on a fixed or mobile platform.

18. The method of claim 11, comprising applying a plurality of fiducials on the object to determine per frame coordinate transformation to accommodate for between frame motion and to align the active sensor surface range data information with a coordinate reference frame that is fixed with respect to the surface of the object.

19. The method of claim 18, wherein the applied fiducials have a distribution on the object'"'"'s surface less than approximately 10,000 fiducials per square millimeter.

20. The method of claim 18, comprising processing fiducial image data using an ego-motion computation technique.