Method for determining the pose of a camera and for recognizing an object of a real environment

• US 10,580,162 B2
• Filed: 01/25/2019
• Issued: 03/03/2020
• Est. Priority Date: 10/19/2009
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Meier, Peter
• Primary Examiner(s): Patel, Nirav G
• Application Number:
  US16/258,110
• Publication Number:
  US 20190172220A1
• Time in Patent Office: 403 Days
• CPC Class Codes: G06T 2207/10012 Stereo images
• CPC Class Codes: G06T 2207/30232 Surveillance
• CPC Class Codes: G06T 2207/30244 Camera pose
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/30 Determination of transform parameters for the alignment of images, i.e. image registration
• CPC Class Codes: G06T 7/33 using feature-based methods
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06T 7/75 involving models
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning
• CPC Class Codes: G06V 10/768 using context analysis, e.g. recognition aided by known co-occurring patterns
• CPC Class Codes: G06V 20/20 in augmented reality scenes
• CPC Class Codes: G06V 20/64 Three-dimensional objects

Abstract

A method for determining the pose of a camera relative to a real environment includes the following steps: taking at least one image of a real environment by means of a camera, the image containing at least part of a real object, performing a tracking method that evaluates information with respect to correspondences between features associated with the real object and corresponding features of the real object as it is contained in the image of the real environment, so as to obtain conclusions about the pose of the camera, determining at least one parameter of an environmental situation, and performing the tracking method in accordance with the at least one parameter. Analogously, the method can also be utilized in a method for recognizing an object of a real environment in an image taken by a camera.

Claims

1. A non-transitory computer readable medium comprising computer readable code which, when executed by one or more processors, causes the one or more processors to:

obtain an image captured by a camera, the image comprising a real environment including a real object;

determine a parameter value of an environmental parameter of the real environment;

select a data model based on a distance between the parameter value and a model parameter value of the environmental parameter associated with the data model; and

detect the real object in the image based on the data model.

2. The non-transitory computer readable medium of claim 1, wherein the computer readable code is further executable by the one or more processors to determine an uncertainty value associated with detection of the real object in the image based on the distance between the parameter value and the model parameter value.

3. The non-transitory computer readable medium of claim 1, wherein the environmental parameter corresponds to a weather condition, a traffic condition, a time of day, an altitude, or a time of year.

4. The non-transitory computer readable medium of claim 1, wherein the computer readable code is further executable by the one or more processors to select an object recognition algorithm based on the parameter value.

5. The non-transitory computer readable medium of claim 4, wherein selecting the object recognition algorithm includes selecting between an edge feature detection algorithm and a corner feature detection algorithm.

6. The non-transitory computer readable medium of claim 1, wherein the computer readable code is further executable by the one or more processors to obtain position data from a position sensor and determine the parameter value based on the position data and environmental report data.

7. The non-transitory computer readable medium of claim 6, wherein the computer readable code is further executable by the one or more processors to obtain the environmental report data from a weather database.

8. The non-transitory computer readable medium of claim 1, wherein detecting the real object in the image based on the data model includes comparing features extracted from the image to the data model.

9. The non-transitory computer readable medium of claim 8, wherein the computer readable code is further executable by the one or more processors to weight comparisons of the features to the data model based on the parameter value.

10. A method comprising:

obtaining an image captured by a camera, the image comprising a real environment including a real object;

determining a parameter value of an environmental parameter of the real environment;

selecting a data model based on a distance between the parameter value and a model parameter value of the environmental parameter associated with the data model; and

detecting the real object in the image based on the data model.

11. The method of claim 10, further comprising determining an uncertainty value associated with detection of the real object in the image based on the distance between the parameter value and the model parameter value.

12. The method of claim 10, wherein the environmental parameter corresponds to a weather condition, a traffic condition, a time of day, an altitude, or a time of year.

13. The method of claim 10, further comprising selecting an object recognition algorithm based on the parameter value.

14. The method of claim 13, wherein selecting the object recognition algorithm includes selecting between an edge feature detection algorithm and a corner feature detection algorithm.

15. The method of claim 10, further comprising obtaining position data from a position sensor and determine the parameter value based on the position data and environmental report data.

16. The method of claim 15, further comprising obtaining the environmental report data from a weather database.

17. An apparatus comprising:

one or more processors; and

one or more memory devices storing instructions executable by the one or more processors to;

obtain an image captured by a camera, the image comprising a real environment including a real object;

determine a parameter value of an environmental parameter of the real environment;

select a data model based on a distance between the parameter value and a model parameter value of the environmental parameter associated with the data model; and

detect the real object in the image based on the data model.

18. The apparatus of claim 17, wherein the instructions are further executable by the one or more processors to determine an uncertainty value associated with detection of the real object in the image based on the distance between the parameter value and the model parameter value.