Motion vector field error estimation

• US 6,442,202 B1
• Filed: 09/14/1998
• Issued: 08/27/2002
• Est. Priority Date: 03/13/1996
• Status: Expired due to Term

• Current Assignee: HBC Solutions Incorporated (AEG Holdings, Inc.)
• Original Assignee: Leitch Europe Limited
• Inventors: Borer, Timothy John
• Primary Examiner(s): Kelley, Chris
• Assistant Examiner(s): VO, TUNG T
• Application Number:
  US09/142,760
• Time in Patent Office: 1,443 Days
• Field of Search: H04/N.732, H04/N.521, H04/B.166, 348/699, 348/413, 348/416, 348/645, 348/85, 348/415, 375/240, 375/240.01, 375/240.03, 375/240.11, 375/240.12, 375/240.13, 375/240.16, 382/236, 382/238, 386/111
• US Class Current: 375/240.16
• CPC Class Codes: G06T 7/269 using gradient-based methods
• CPC Class Codes: H04N 19/51 Motion estimation or motion compensation
• CPC Class Codes: H04N 5/145 Movement estimation for video coding H04N19/51

Abstract

A technique is disclosed for estimating the measurement error in motion vectors used for example in a motion compensated video signal process. For each motion vector corresponding to a region of an image a plurality of temporal and spatial image gradients are calculated corresponding to that region. From the constraint equations of the image gradients a plurality of error values can be calculated for each motion vector and a parameter generated describing the size of the distribution of motion vector measurement errors. Subsequent processing of the video signals using the motion vectors can then be adapted, for example by graceful fallback in motion compensated interpolation, depending on the accuracy of each motion vector. The ‘confidence’ in the accuracy of each motion vector can be described by a parameter calculated in relation to the size of the error distribution and the motion vector speed.

Claims

1. Video or film signal processing apparatus comprising:

a motion estimation apparatus for generating best fit motion vectors, each best fit motion vector corresponding to a region of an input signal,

a means for calculating, for each of said regions of the input signal, a plurality of spatial and temporal image gradients,

a means for calculating, for each said best fit motion vector, a plurality of error values corresponding to said plurality of image gradients,

a means for calculating a plurality of error vectors from said plurality of error values,

a logic means adapted to calculate for each motion vector an estimate of the distribution of vector measurement errors in calculating said best fit motion vector, and

a means adapted to generate, for each said motion vector, an indication of the motion vector measurement error derived from said estimate.

2. Video or film signal processing apparatus as claimed in claim 1, wherein said logic means provides, for each motion vector, a statistical analysis of the error in the constraint equation for each of a plurality of pixels in a region of the input signal.

3. Video or film signal processing apparatus as claimed in claim 1, wherein said logic means provides, for each motion vector, a matrix representing the dimensions and orientation of the error distribution.

4. Video or film signal processing apparatus as claimed in claim 1, wherein the apparatus includes means for calculating the elements of an error matrix from said error vectors, said matrix representing the distribution of motion vector measurements errors.

5. Video or film signal processing apparatus as claimed in claim 4, wherein the apparatus further includes means for performing an eigenvector analysis on said error matrix or on on covariance matrix for the measured motion vector.

6. Video or film signal processing apparatus comprising:

a motion estimation apparatus for generating best fit motion vectors, each best fit motion vector corresponding to a region of an input signal,

a means for calculating, for each of said regions of the input signal, a plurality of spatial and temporal image gradients,

a means for calculating, for each said best fit motion vector, a plurality of error values corresponding to said plurality of image gradients,

a means for calculating a plurality of error vectors from said plurality of error values,

a logic means adapted to calculate for each motion vector, an estimate of the distribution of vector measurement errors in calculating said best fit motion vector, and

a means adapted to generate, for each said vector, an indication of the motion vector measurement error derived from said estimate,

wherein the apparatus includes means for calculating the standard deviation of the error in the constraint equations for each of a plurality of pixels in a region of said input signal, and means for estimating the error in measuring the motion vector using the resultant standard deviation, and

wherein an estimate of the covariance matrix for the measured motion vector is generated, the covariance matrix having vector components.

7. Video or film signal processing apparatus as claimed in claim 6, wherein the apparatus further includes means for performing an eigenvector analysis on said error matrix or on said covariance matrix.

8. A method of video or film signal processing comprising the steps of:

generating best fit motion vectors corresponding to plural regions of an input signal,

calculating, for each of said plural regions of the input signal, a plurality of spatial and temporal image gradients,

calculating, for each said best fit motion vector, a plurality of error values corresponding to said plurality of image gradients,

calculating a plurality of error vectors from said plurality of error values,

calculating, for each motion vector, an estimate of the distribution of vector measurement errors in calculating said best fit motion vector, and

generating, for each said motion vector, an indication of the motion vector measurement error derived from said estimate.

9. A method of video or film signal processing apparatus as claimed in claim 8, wherein said step of calculating provides, for each vector, a statistical analysis of the error in the constraint equation for each of said pixels.

10. A method of video or film signal processing as claimed in claim 8, wherein said step of calculating provides, for each motion vector, a matrix representing the dimensions and orientation of the error distribution.

11. A method of video or film signal processing as claimed in claim 8, wherein the method includes the step of calculating the elements of an error matrix from said error vectors said matrix representing the distribution of motion vector measurement errors.

12. A method of video or film signal processing as claimed in claim 11, wherein the method further includes performing an eigenvector analysis on said error matrix or on a covariance matrix for the measured motion vector.

13. A method of video or film signal processing as claimed in claim 8, wherein the method includes calculating the standard deviation of the error in the constraint equations for each of a plurality of pixels in a region of said input signal, and estimating the error in measuring the motion vector using the resultant standard deviation, whereby an estimate of the covariance matrix for the measured motion vector is generated.

14. A method of video or film signal processing as claimed in claim 13, wherein the method further includes performing an eigenvector analysis on said error matrix or on said covariance matrix.