IP Library Granted Patent US 9,152,879
Granted Patent B2
US 9,152,879 · App. 14/249,295 · Granted Oct 6, 2015

Keypoint descriptor generation by complex wavelet analysis

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Quick Facts
Patent No.
US 9,152,879
App. No.
14/249,295
Granted
Oct 6, 2015
Kind
B2
Abstract

The present application relates to a method of generating a keypoint descriptor for identifying an object in an image or a sequence of images, the keypoint descriptor being substantially invariant to a transformation of the object in the image. The method includes receiving object data representing an object for identification in an image; processing the object data to generate at least one basis function representing a feature having undergone at least one transformation or a transformation sequence across several consecutive frames, optionally using transformations that are out of a plane of the image to recognize objects from multiple views; modifying a prototype wavelet function based on the at least one basis function to generate a plurality of modified wavelet functions; comparing the plurality of modified wavelet functions with the at least one basis function; selecting a modified wavelet function of the plurality of modified wavelet functions based on the comparison of the plurality of modified wavelet functions with the at least one basis function; and processing an input image or input orientation field according to the selected modified wavelet function to generate the keypoint descriptor. The present application further relates to a method of identifying an object in an image using a keypoint descriptor; and processing apparatus and computer program products for implementing a method of the present application.

Claims (45)

1. A method of generating a keypoint descriptor for identifying an object in an image, wherein the keypoint descriptor is substantially invariant to a transformation of the object in the image, the method comprising:

receiving object data indicative of an object for identification in an image, the image having an image plane associated therewith;

generating, by processing the received object data, at least one basis function representing a feature having undergone at least one transformation, using transformations that are out of the image plane to recognize objects from multiple views;

modifying a prototype wavelet function based on the at least one basis function to generate a plurality of modified wavelet functions;

comparing the plurality of modified wavelet functions with the at least one basis function;

selecting a modified wavelet function of the plurality of modified wavelet functions based on the comparison of the plurality of modified wavelet functions with the at least one basis function; and

generating the keypoint descriptor by processing at least one of an input image or an input orientation field according to the selected modified wavelet function to,

wherein the object is a three-dimensional object in a three-dimensional image and the keypoint descriptor is configured to identify an object in a series of images spaced over time, and

wherein the prototype wavelet function and the plurality of modified wavelet functions comprise a radial distance component, and azimuthal angle component and a polar angle component, the prototype wavelet function and the plurality of modified wavelet functions having the formula;

Ψ k ( d ,θ,φ)= d n k −1 e −α k d ( n k −α k d )·(cos( m k θ)+ q x sin( m k θ))·(cos( l k φ)+ q y sin( l k φ))

where the term d n k −1 e −α k d (n k −α k d) is the radial distance weighting component with radial distance, d, the term (cos(m k θ)+q x sin(m k θ)) is the azimuthal angle component with azimuthal angle θ, and the term (cos(l k φ)+q y sin(l k φ)) is the polar angle component with polar angle Ψ, and where the terms q x and q y denote unit quaternions and obey the rules q x 2 =q y 2 =q z 2 =−1, and q x q y =q z .

2. The method of claim 1 , wherein the keypoint descriptor is configured to identify an object in a single image.

3. The method of claim 2 , wherein the object is a two-dimensional or three-dimensional object in a two-dimensional image.

4. The method of claim 1 , wherein the prototype wavelet function and the plurality of modified wavelet functions comprise a radial distance component and an azimuthal angle component.

5. The method of claim 4 , wherein the prototype wavelet function and the modified wavelet functions comprise a non-linear weighting of the radial distance component.

6. The method of claim 5 , wherein the non-linear weighting represents a radial decay.

7. The method of claim 1 , wherein the comparing of the plurality of modified wavelet functions with the at least one basis function includes matching at least one of the modified wavelet functions with the at least one basis function, and the selecting of the modified wavelet function of the plurality of modified wavelet functions based on the comparison of the plurality of modified wavelet functions with the at least one basis function is selected according to matching criteria.

8. The method of claim 7 , wherein the processing of the object data includes generating a plurality of basis functions, the comparing of the plurality of modified wavelet functions with the at least one basis function includes matching a number of the plurality of basis functions with at least one of the modified wavelet functions, and the selecting of the modified wavelet function of the plurality of modified wavelet functions based on the comparison of the plurality of modified wavelet functions with the at least one basis function includes selecting a modified wavelet function for each of the number of the plurality of basis functions according to matching criteria.

9. The method of claim 8 , wherein the keypoint descriptor is generated when selecting a modified wavelet function of the plurality of modified wavelet functions based on the selected wavelet functions.

10. A system for generating a keypoint descriptor, comprising:

a data store comprising executable software;

a processor in data communication with the data store, the processor configured to execute the software and cause a computing device to:

receive object data representing an object for identification in an image;

process the object data to generate at least one basis function representing a feature having undergone at least one transformation or a transformation sequence across several consecutive frames, optionally using transformations that are out of a plane of the image to recognize objects from multiple views;

modify a prototype wavelet function based on the at least one basis function to generate a plurality of modified wavelet functions;

compare the plurality of modified wavelet functions with the at least one basis function;

select a modified wavelet function of the plurality of modified wavelet functions based on the comparison of the plurality of modified wavelet functions with the at least one basis function; and

process an input image or input orientation field according to the selected modified wavelet function to generate a keypoint descriptor,

wherein the object is a three-dimensional object in a three-dimensional image and the keypoint descriptor is configured to identify an object in a series of images spaced over time, and

wherein the prototype wavelet function and the plurality of modified wavelet function comprise a radial distance component, and azimuthal angle component and a polar angle component, the prototype wavelet function and the plurality of modified wavelet functions having the formula:

Ψ k ( d,θ,φ )= d n k −1 e −α k d ( n k −α k d )·(cos( m k θ)+ q x sin( m k θ))·(cos( l k φ)+ q y sin( l k φ))

where the term d n k −1 e −α k d (n k −α k d) is the radial distance weighting component with radial distance, d, the term (cos(m k θ)+q x sin(m k θ)) is the azimuthal angle component with azimuthal angle θ, and the term (cos(l k φ)+q y sin(l k φ)) is the polar angle component with polar angle Ψ, and where the terms q x and q y denote unit quaternions and obey the rules q x 2 =q y 2 =q z 2 =−1, and q x q y =q z .

11. The system of claim 10 , wherein the processor is further configured to execute the executable software and cause the system to process image data representing at least part of the image using the generated keypoint descriptor.

12. A non-transitory computer-readable storage medium having computer readable instructions stored thereon, wherein, when executed, cause the computerized device to perform a method of generating a keypoint descriptor for identifying an object in an image or in a sequence of images, wherein keypoint descriptor is substantially invariant to a transformation of the object in the image, the method comprising:

receiving object data representing an object for identification in an image;

processing the object data to generate at least one basis function representing a feature having undergone at least one transformation or a transformation sequence across several consecutive frames, optionally using transformations that are out of a plane of the image to recognize objects from multiple views;

modifying a prototype wavelet function based on the at least one basis function to generate a plurality of modified wavelet functions;

comparing the plurality of modified wavelet functions with the at least one basis function;

selecting a modified wavelet function of the plurality of modified wavelet functions based on the comparison of the plurality of modified wavelet functions with the at least one basis function; and

processing an input image or input orientation field according to the selected modified wavelet function to generate the keypoint descriptor,

wherein the object is a three-dimensional object in a three-dimensional image and the keypoint descriptor is configured to identify an object in a series of images spaced over time, and

wherein the prototype wavelet function and the plurality of modified wavelet functions comprise a radial distance component, and azimuthal angle component and a polar angle component, the prototype wavelet function and the plurality of modified wavelet functions having the formula:

Ψ k ( d ,θ,φ)= d n k −1 e −α k d ( n k −α k d )·(cos( m k θ)+ q x sin( m k θ))·(cos( l k φ)+ q y sin( l k φ))

where the term d n k −1 e −α k d (n k −α k d) is the radial distance weighting component with radial distance, d, the term (cos(m k θ)+q x sin(m k θ)) is the azimuthal angle component with azimuthal angle θ, and the term (cos(l k φ)+q y sin(l k φ)) is the polar angle component with polar angle Ψ, and where the terms q x and q y denote unit quaternions and obey the rules q x 2 =q y 2 =q z 2 =−1, and q x q y =q z .

13. The non-transitory computer-readable storage medium of claim 12 , wherein the method further comprises including processing image data representing at least part of the image with a keypoint descriptor.

Assignments (6)
SECURITY INTEREST Recorded Apr 12, 2021
From: ZEBRA TECHNOLOGIES CORPORATION
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 056471/0906 →
RELEASE OF SECURITY INTEREST - 364 - DAY Recorded Mar 5, 2021
From: JPMORGAN CHASE BANK, N.A.
To: ZEBRA TECHNOLOGIES CORPORATION; LASER BAND, LLC; TEMPTIME CORPORATION
Reel/Frame 056036/0590 →
SECURITY INTEREST Recorded Sep 1, 2020
From: ZEBRA TECHNOLOGIES CORPORATION; LASER BAND, LLC; TEMPTIME CORPORATION
To: JPMORGAN CHASE BANK, N.A.
Reel/Frame 053841/0212 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 21, 2020
From: CORTEXICA VISION SYSTEMS LIMITED
To: ZEBRA TECHNOLOGIES CORPORATION
Reel/Frame 051565/0873 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 31, 2015
From: BHARATH, ANIL ANTHONY; NG SING KWONG, JEFFREY
To: IMPERIAL INNOVATIONS LTD
Reel/Frame 036462/0343 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 31, 2015
From: IMPERIAL INNOVATIONS LIMITED
To: CORTEXICA VISION SYSTEMS LIMITED
Reel/Frame 036462/0349 →