Method and apparatus for generating three-dimensional pose using monocular visual sensor and inertial measurement unit

• US 8,761,439 B1
• Filed: 08/24/2011
• Issued: 06/24/2014
• Est. Priority Date: 08/24/2011
• Status: Active Grant

• Current Assignee: SRI International, Inc.
• Original Assignee: SRI International, Inc.
• Inventors: Kumar, Rakesh, Samarasekera, Supun, Oskiper, Taragay
• Primary Examiner(s): GORADIA, SHEFALI DINESH
• Application Number:
  US13/217,014
• Time in Patent Office: 1,035 Days
• Field of Search: None
• US Class Current: 382/103
• CPC Class Codes: G06T 7/73 using feature-based methods

Abstract

An apparatus for providing three-dimensional pose comprising monocular visual sensors for providing images of an environment surrounding the apparatus, an inertial measurement unit (IMU) for providing gyroscope, acceleration and velocity information, collectively IMU information, a feature tracking module for generating feature tracking information for the images, and an error-state filter, coupled to the feature track module, the IMU and the one or more visual sensors, for correcting IMU information and producing a pose estimation based on at least one error-state model chosen according to the sensed images, the IMU information and the feature tracking information.

Claims

1. An apparatus for providing a three-dimensional pose data-stream comprising:

one or more monocular visual sensors for providing images of an environment surrounding the apparatus;

an inertial measurement unit (IMU) for providing gyroscope, acceleration and velocity information, collectively referred to as IMU information;

a feature tracking module for generating feature track information for the images;

one or more global tracking units for providing global location information; and

a landmark matcher, coupled to the feature tracking module, for generating an error state derived from comparing feature locations from at least one image to a visual landmark within the environment; and

an error-state filter, coupled to the feature tracking module, the IMU, the one or more global tracking units, the landmark matcher and the one or more visual sensors, for correcting the IMU information and the global location information and producing a pose estimation based on at least one error-state model chosen according to the images, the IMU information, the global location information and the feature tracking information.

2. The apparatus of claim 1 further comprising:

a magnetometer unit, coupled to the error-state filter, for providing magnetic field information; and

wherein the error-state filter also corrects the magnetic field information.

3. The apparatus of claim 2 wherein successive readings of the magnetometer unit are compared to the IMU information and to a nominal magnetic field providing error correction for the error-state filter.

4. The apparatus of claim 2 wherein the global location information is combined with the IMU information for generating an accurate global position and heading fix.

5. The apparatus of claim 4 wherein the accurate global position and heading initializes a global heading direction for the apparatus and a bias for the magnetometer unit.

6. The apparatus of claim 1 wherein the one or more visual sensors comprise one or more monocular cameras and one or more stereo cameras.

7. The apparatus of claim 1 wherein the error-state model of the error-state filter is selected as comprising at least one of an epipolar constraint model, a reprojection constraint model and a rotation-only model, based on parameters provided to the error-state filter.

8. The apparatus of claim 7 where the parameters are at least one of light levels, directional velocity and rotation from the IMU.

9. The apparatus of claim 8 wherein the error-state model is set to the epipolar model when at least one of the light levels are low, the IMU detects a directional velocity, and the apparatus is initializing.

10. The apparatus of claim 8 wherein the error-state model is set to the rotation-only model when only rotation is detected.

11. The apparatus of claim 8 wherein the error-state model is set to the reprojection model when the apparatus is in a steady state which comprises at least one of normal light levels, regular IMU information and apparatus initialization.

12. The apparatus of claim 1 further comprising an output processor for generating, based on the pose estimation, at least one of tracking information or an augmented reality display.

13. The apparatus of claim 1 wherein the apparatus is attached to a mobile device.

14. The apparatus of claim 1 wherein the apparatus is attached to eyewear.

15. The apparatus of claim 1 wherein results of the error-state filter are coupled to the IMU for producing a final error-corrected pose estimation.

16. A computer implemented method for generating a three-dimensional pose estimation comprising:

sensing images of a surrounding environment using a monocular visual sensor;

providing gyroscope, acceleration and velocity information, collectively referred to as IMU information;

providing location information for tracking global coordinates;

matching the images to visual landmarks; and

tracking features in the images for providing inliers of the images; and

generating an error correction for the IMU information and the location information and generating a pose estimation based on the sensed images, the IMU information, the location information and the inliers of the images.

17. The method of claim 16 further comprising:

measuring and providing magnetic field information; and

generating the error correction for the magnetic field information.

18. The method of claim 16 wherein the generating a pose estimation comprises selecting between a reprojection model, an epipolar model or a rotation-only model based on light levels and the IMU information.

19. The method of claim 18 wherein the reprojection model is selected when light levels and the IMU information are in a steady state, the epipolar model is selected when light levels are low and the IMU information is providing directional velocity, and the rotational-only model is selected when the IMU information provides zero velocity.

20. The method of claim 19 wherein the pose estimation is coupled with the images of surrounding environment to create an augmented reality display overlaying the images with contextual data.

21. An apparatus for providing a three-dimensional pose data-stream comprising:

one or more monocular visual sensors for providing images of an environment surrounding the apparatus;

an inertial measurement unit (IMU) for providing gyroscope, acceleration and velocity information, collectively referred to as IMU information;

a feature tracking module for generating feature track information for the images;

an error-state smoother, coupled to the feature tracking module, the IMU and the one or more visual sensors, for correcting the IMU information and producing a pose estimation based on at least one error-state model chosen according to the images, the IMU information and the feature tracking information; and

wherein the error-state model of the error-state smoother is selected as comprising at least one of an epipolar constraint model, a reprojection constraint model and a rotation-only model, based on parameters provided to the error-state smoother.

22. An apparatus for providing a three-dimensional pose data-stream comprising:

one or more monocular visual sensors for providing images of an environment surrounding the apparatus;

an inertial measurement unit (IMU) for providing gyroscope, acceleration and velocity information, collectively referred to as IMU information;

a feature tracking module for generating feature track information for the images;

a magnetometer for providing magnetic field information;

an error-state filter, coupled to the feature tracking module, the IMU, the magnetometer and the one or more visual sensors, for correcting the IMU information and the magnetic field information and producing a pose estimation based on at least one error-state model chosen according to the images, the IMU information, the magnetic field information and the feature tracking information; and

wherein successive readings of the magnetometer are compared to the IMU information and to a nominal magnetic field providing error correction for the error-state filter.

23. A computer implemented method for generating a three-dimensional pose estimation comprising:

sensing images of a surrounding environment using a monocular visual sensor;

providing gyroscope, acceleration and velocity information, collectively referred to as IMU information;

tracking features in the images for providing inliers of the images;

generating an error correction for the IMU information and a pose estimation based on the sensed images, the IMU information and the inliers of the images; and

wherein the generating a pose estimation comprises selecting between a reprojection model, an epipolar model or a rotation-only model based on light levels and the IMU information.