INTRINSIC FEATURE-BASED POSE MEASUREMENT FOR IMAGING MOTION COMPENSATION

• US 20120293667A1
• Filed: 05/16/2011
• Published: 11/22/2012
• Est. Priority Date: 05/16/2011
• Status: Active Grant

• Current Assignee: UT-Battelle LLC
• Original Assignee: UT-Battelle LLC
• Inventors: Baba, Justin S., Goddard, James Samuel Jr.
• Granted Patent: US 8,810,640 B2
• Time in Patent Office: Days
• US Class Current: 348/187
• CPC Class Codes: G06T 2207/10021 Stereoscopic video; Stereoscopic image sequence
• CPC Class Codes: G06T 2207/10108 Single photon emission computed tomography [SPECT]
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/30004 Biomedical image processing
• CPC Class Codes: G06T 7/251 involving models
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters
• CPC Class Codes: G06T 7/75 involving models
• CPC Class Codes: H04N 13/246 Calibration of cameras
• CPC Class Codes: H04N 2013/0085 Motion estimation from stereoscopic image signals
• CPC Class Codes: H04N 7/00 Television systems details H04N3/00, H04N5/00; methods or arrangements, for coding, decoding, compressing or decompressing digital video signals H04N19/00; selective content distribution H04N21/00
• CPC Class Codes: H04N 7/01 Conversion of standards , e.g. involving analogue television standards or digital television standards processed at pixel level

Abstract

Systems and methods for generating motion corrected tomographic images are provided. A method includes obtaining first images of a region of interest (ROI) to be imaged and associated with a first time, where the first images are associated with different positions and orientations with respect to the ROI. The method also includes defining an active region in the each of the first images and selecting intrinsic features in each of the first images based on the active region. Second, identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of second images of the ROI associated with a second time prior to the first time and computing three-dimensional (3D) coordinates for the portion of the intrinsic features. Finally, the method includes computing a relative pose for the first images based on the 3D coordinates.

Claims

1. A method for generating pose information for motion correcting images, comprising the steps of:

obtaining a first plurality of images of a region of interest (ROI) to be imaged, the first plurality of images associated with a first time and with different positions and orientations with respect to the ROI;

defining active regions in each of the first plurality of images, selecting intrinsic features in each of the first plurality of images based on the corresponding ones of the active regions,

identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of a second plurality of images of the ROI associated with a second time prior to the first time, and

computing a relative pose for the first plurality of images based on the portion of the intrinsic features.

2. The method of claim 1, wherein the step of obtaining comprises:

rectifying a plurality of raw images acquired using a plurality of cameras at the different positions to a canonical arrangement based on calibration parameters for the plurality of cameras to yield the first plurality of images.

3. The method of claim 2, wherein the step of obtaining further comprises:

prior to the rectifying, adjusting image attributes for the plurality of raw images.

4. The method of claim 2, wherein the rectifying comprises:

applying an image rectification transform to each of the plurality of raw images based on the calibration parameters to yield a plurality of rectified images that lie in a same plane, have a same focal length, and have a same orientation.

5. The method of claim 2, wherein the rectifying comprises:

applying an image rectification transform to the plurality of raw images based on the calibration parameters to yield a plurality of rectified images so that each of the intrinsic features in the plurality of images lies along at least one of a common horizontal line and a common vertical line,

6. The method of claim 1, wherein the defining the active region further comprises:

selecting as the active regions visible portions of the ROI extracted from the first plurality of images.

7. The method of claim 1, wherein the selecting the intrinsic features further comprises:

selecting as the intrinsic features a portion of discrete features extracted from the one of the first plurality of images located in the active region.

9. The system of claim 1, wherein the first module is further configured for causing the processor to rectify a plurality of raw images acquired using a plurality of cameras at the different positions to a canonical arrangement based on calibration parameters for the plurality of cameras to yield the first plurality of images.

10. The system of claim 9, the first module is further configured for causing the processor to adjust image attributes for the plurality of raw images prior to the rectifying.

11. The system of claim 9, wherein rectifying the plurality of raw images comprises:

applying an image rectification transform to each of the plurality of raw images based on the calibration parameters to yield a plurality of rectified images that lie in a same plane, have a same focal length, and have a same orientation.

12. The system of claim 9, wherein the rectifying the plurality of raw images comprises:

applying an image rectification transform to each of the plurality of raw images based on the calibration parameters to yield a plurality of rectified images.

16. The computer-readable medium of claim 1, wherein the obtaining comprises:

adjusting image attributes for a plurality of raw images of the ROI acquired using a plurality of cameras at the different positions; and

rectifying the plurality of raw images to a canonical arrangement based on calibration parameters for the plurality of cameras to yield the first plurality of images.

17. The computer-readable medium of claim 16, wherein the rectifying comprises:

applying an image rectification transform to each of the plurality of raw images based on the calibration parameters to yield a plurality of rectified images that lie in a same plane, have a same focal length, and have a same orientation.

18. The computer-readable medium of claim 16, wherein the rectifying comprises:

applying an image rectification transform to the plurality of raw images based on the calibration parameters to yield a plurality of rectified images so that each of the intrinsic features in the plurality of images lies along at least one of a common horizontal line and a common vertical line.

8. A system for generating pose information for motion correcting images, comprising:

a processor;

a first module configured for causing the processor to obtain a first plurality of images of a region of interest (ROD to be imaged, the first plurality of images associated with a first time and with different positions and orientations with respect to the ROI;

a second module configured for causing the processor to define active regions in each of the first plurality of images,

a third module configured for causing the processor to select intrinsic features in each of the first plurality of images based on the corresponding ones of the active regions, a fourth module configured for causing the processor to identify a portion of the intrinsic features temporally and spatially matching intrinsic features in corresponding ones of a second plurality of images of the ROI associated with a second time prior to the first time, and a fifth module configured for causing the processor to compute a relative pose for the first plurality of images based on the portion of the intrinsic features.

13. The system of claim 8, wherein the second module is further configured for causing the processor to define the active regions by selecting as the active regions visible portions of the ROI extracted from the first plurality of images.

14. The system of claim 8, wherein the third module is further configured for causing the processor to select the intrinsic features by selecting as the intrinsic features a portion of discrete features extracted from the one of the first plurality of images located in the active region.

15. A computer-readable medium storing a computer program having instructions for generating pose information for motion correcting images, the instructions comprising:

obtaining a first plurality of images of a region of interest (ROI) to be tomographically imaged and associated with a first time, the first plurality of images associated with different positions and orientations with respect to the ROI;

processing each one of the first plurality of images, the processing comprising

defining an active region in the one of the first plurality of images,

selecting intrinsic features in the one of the first plurality of images based on the active region,

identifying a portion of the intrinsic features temporally and spatially matching intrinsic features in a corresponding one of a second plurality of images of the ROI associated with a second time prior to the first time, and

computing three-dimensional (3D ) coordinates for the portion of the intrinsic features; and

computing a relative pose for the first plurality of images based on the 3D coordinates.

19. The computer-readable medium of claim 15, wherein the defining the active region further comprises:

selecting as an outline of the active region a visible portion of the ROI extracted from the one of the first plurality images.

20. The computer-readable medium of claim 15, wherein the selecting the intrinsic features further comprises:

selecting as the intrinsic features a portion of discrete features extracted from the one of the first plurality of images located in the active region.