METHOD FOR GENERATING AN ARRAY OF 3-D POINTS

• US 20140078260A1
• Filed: 09/19/2013
• Published: 03/20/2014
• Est. Priority Date: 09/20/2012
• Status: Active Grant

• Current Assignee: Brown University
• Original Assignee: Brown University
• Inventors: Taubin, Gabriel, Moreno, Daniel
• Granted Patent: US 10,008,007 B2
• Time in Patent Office: Days
• US Class Current: 348/46
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 7/521 from laser ranging, e.g. using interferometry; from the projection of structured light
• CPC Class Codes: G06T 7/80 Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
• CPC Class Codes: G06T 7/85 Stereo camera calibration
• CPC Class Codes: H04N 13/246 Calibration of cameras

Abstract

A method that estimates the coordinates of the calibration points in the projector image plane using local homographies obtained from the imaging camera. First, a dense set of correspondences between projector and camera pixels is found by projecting onto the calibration object an identical pattern sequence as the one later projected when scanning the target, reusing most of the software components written for the scanning application. Second, the set of correspondences is used to compute a group of local homographies that allow projection back of any of the points in the calibration object onto the projector image plane with sub-pixel precision. In the end, the data projector is then calibrated as a normal camera.

Claims

1. A method of calibrating a system for capturing a 3-D array of points comprising:

providing a camera and projector directed at an image capture field;

placing an imaging plane containing a plurality of identifiable points thereon at a plurality of orientations within the image capture field;

projecting a sequence of structured-light patterns onto said imaging plane;

capturing a series of images of said imaging plane each image corresponding each of said structured-light patterns in said sequence;

repeating said projecting and capturing steps to generate a series of images for each of said plurality of orientations of said imaging plane; and

estimating calibration parameters for the camera and projector from the series of images for each of said plurality of orientations of said imaging plane.

2. The method of claim 1, wherein each of said image series are saved at a location separate from one another.

3. The method of claim 1, wherein one of said structured-light patterns is full illumination of the imaging plane.

4. The method of claim 1, wherein the imaging plane is a checkerboard of known dimensions and said identifiable points are corners of said checkerboard.

5. The method of claim 4, wherein the camera is calibrated by computing a relationship between the identifiable points in the camera images and actual identifiable point positions in the imaging field.

6. The method of claim 4, wherein the projector is calibrated by:

associating pixels within each of the captured images with a row and column within the projector;

estimating a homography for each identifiable point in the captured image; and

converting each identifiable point from camera coordinates to projector coordinates using said homography

7. The method of claim 6, wherein said homography is a local homography that is created for each identifiable point.

8. An algorithm for calibrating an image capturing system comprising a camera, a projector and an imaging field, said algorithm comprising the steps of:

using said camera detect identifiable points in a series of captured images of a imaging plane containing a plurality of identifiable points positioned at a plurality of orientations within said imaging field;

capture images of said imaging plane at a plurality of orientations within said imaging field while applying a series of structured light patterns;

decode pixels in said captured images into projector row and column correspondences;

compute a local homography that converts from camera to projector coordinates using small image patches centered at the identifiable point coordinates;

translate corner locations from camera to projector coordinates using said local homographies;

fix a world coordinate system to the imaging plane and find camera intrinsics using camera identifiable point locations and find projector intrinsics using projector identifiable point locations; and

fix camera and projector intrinsics and use world, camera, and projector identifiable point locations to estimate stereo extrinsic parameters.

9. The method of claim 8, the step of decoding pixels further comprising:

estimate global and direct light components for each set using high frequency structured light patterns.