TARGET AND METHOD OF DETECTING, IDENTIFYING, AND DETERMINING 3-D POSE OF THE TARGET

• US 20130259304A1
• Filed: 03/12/2013
• Published: 10/03/2013
• Est. Priority Date: 10/14/2008
• Status: Active Grant

• Current Assignee: Jolly Seven, Series 70 of Allied Security Trust I (Allied Security Trust)
• Original Assignee: Spot Vision LLC
• Inventors: Aller, Joshua Victor
• Granted Patent: US 9,002,062 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: B42D 15/00 Printed matter of special format or style not otherwise provided for
• CPC Class Codes: G06T 2207/30204 Marker
• CPC Class Codes: G06T 7/73 using feature-based methods
• CPC Class Codes: G06V 10/245 by locating a pattern; Special marks for positioning

Abstract

We disclose a photogrammetry target that includes a background having a first color and a plurality of ovoid regions located on the background and having a second color contrasting the first color. We further disclose a method and system for detecting the target and processing image data captured from the target to discern therefrom at least one of a distance to the target, identification of the target, or pose of the target.

Claims

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21. A target, comprising:

a background shape,

a plurality of foreground ovoids arranged in the background shape and configured to allow a linear scaling transform that when applied to the background shape and at least one foreground ovoid converts the at least one foreground ovoid between a set of model space parameters and a set of rotationally non-symmetric metric space parameters assigned to the set of model space parameters, the plurality of foreground ovoids further arranged to identify the target and uniquely identify each of the foreground ovoids.

22. The target of claim 21 wherein the plurality of foreground ovoids are positioned to achieve a maximum separation within the offset background shape.

23. The target of claim 21 further comprising additional features outside of the background shape configured to aid in the detection of the orientation of the target.

24. The target of claim 21 wherein the plurality of ovoids are ellipses configured to differentiate and identify the target, each having one or more metric space parameters from the group of size, aspect ratio, and orientation.

25. The target of claim 21 wherein the offset background shape has a background area and the plurality of foreground ovoids have a total area related to the background area by a predetermined total area to background area ratio.

26. The target of claim 21 wherein the plurality of foreground ovoids are chosen from a fixed pallet of various size and shapes configured to allow encoding of digital information without having to identify each plurality of foreground ovoid shape or pattern of placement of the plurality of foreground ovoids.

27. The target of claim 21 wherein at least two of the plurality of foreground ovoids have a different light intensity color.

28. The target of claim 27 wherein the each of the different light intensity colors encode substantially the same luminance light intensity and configured to allow detection by at least one of a color camera and a black and white camera.

29. The target of claim 21 wherein the metric space parameters includes a parameter from the group of fractional area of background, aspect ratio, rotational ordering, distance between center of background shape to center of respective ovoid, angle between respective ovoid and next respective ovoid, and alignment of spokes created between center of background and respective center of plurality of ovoids.

30. The target of claim 21 wherein at least one foreground ovoid has an eccentricity greater than one and the metric space parameters includes an angle between a major axis of the at least one foreground ovoid and a spoke defined from the center of the background shape to the center of the at least one foreground ovoid.

31. A target detection system, comprising:

an image receiver configured to receive an image with a set of pixels representing a target having a background and a plurality of foreground ovoids; and

an ovoid detector coupled to the image receiver including,

a schema,

a model space convertor configured to extract a set of rotationally non-symmetric metric space parameters from the plurality of foreground ovoids and compare to metrics space parameters associated with at least one shape in the schema, and

a shape matching and marker identifier coupled to the schema and the model space convertor configured to detect an id of the target.

32. The system of claim 32 further comprising an area ratio adjustment module coupled to the schema, the area ratio adjustment module including a boundary shift compensation module configured to match an area ratio of a target shape within the set of pixels from the schema.

33. The system of claim 32 further comprising a multi-part shape detector configured to detect ellipses with a contouring method that extracts at least one iso-contour polygon from the set of pixels in the image provided by the image receiver.

34. The system of claim 33 wherein the contouring method uses a triangular lattice superimposed over the set of pixels of the image, the triangles of the triangular lattice having vertices on at least one of pixel centers and pixel corners.

35. The system of claim 34 wherein the at least one iso-contour polygon is extracted by selecting an intensity value within the set of pixels and linear interpolation is used between three corners of a triangle to find a directed line segment that represent the crossing of the intensity value within the triangle.

36. The system of claim 33 wherein a center of mass is determined by the multi-part shape detector and a unit circle is centered within the iso-contour polygons and a first matrix of points on the at least one iso-contour polygon is used with a second matrix of points on the unit circle to create a linear transform matrix that represents a fit between the points in the first and second matrices.

37. The system of claim 36 wherein minor and major axes of a detected ellipse is determined by extracting eigenvectors and eigenvalues from the linear transform matrix.

38. The system of claim 32, where in the target is located within a fiducial marker and the shape matching and marker identifier is further configured to detect 2-D markers in the fiducial marker outside of the target and the target is configured to encode the fiducial coding system and location of the 2-D markers.

39. The system of claim 32 further comprising a 3-D position and orientation extractor coupled to the shape matching and marker identifier configured to determine a 3-D pose of the target.

40. One or more non-transitory computer-readable media storing computer-executable instructions, which when executed perform steps, comprising:

receiving an image with a set of pixels representing a target having a background and a plurality of foreground ovoids;

detecting an ovoid within the image with a model space convertor by,

matching a shape and marker of the ovoid using a schema, and

extracting and comparing a set of rotationally non-symmetric metric space parameters from the plurality of foreground ovoids to metrics space parameters associated with at least one shape in the schema; and

detecting an id of the target based on the model space convertor and the schema.