Analyzing motion of characteristics in images

• US 7,545,957 B2
• Filed: 04/20/2001
• Issued: 06/09/2009
• Est. Priority Date: 04/20/2001
• Status: Expired due to Term

• Current Assignee: Avid Technology Incorporated
• Original Assignee: Avid Technology Incorporated
• Inventors: Fayan, Randy M., Cornog, Katherine H.
• Primary Examiner(s): TUCKER, WESLEY J
• Application Number:
  US09/839,044
• Publication Number:
  US 20020154792A1
• Time in Patent Office: 2,972 Days
• Field of Search: 382/104, 382/103, 382/107
• US Class Current: 382/107
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments

Abstract

In calculating motion between two images, a single channel image may be generated for each image based on measurement of a desired characteristic of those images. Given a desired characteristic (such as edge strength or edge magnitude) in an image, a function measures the strength of the desired characteristic in a region around a pixel in an image. A range of values can represent the likelihood, or measure of confidence, of the occurrence of the desired characteristic in the region around the pixel. Thus, each pixel in the single channel image has a value from the range of values that is determined according to a function. This function operates on a neighborhood in the input image that corresponds to the pixel in the single channel image, and measures the likelihood of occurrence of, or strength of, the desired characteristic in that neighborhood. Two single channel images generated from two input images are analyzed to provide a motion estimate that indicates how the location of characteristics in the images changes from one image to the next image. If the desired characteristic is an edge magnitude or edge strength, then the motion is effectively estimated using a constant edge constraint.

Claims

1. A method for applying a motion effect using two input images, comprising:

generating a single channel image for each of two input images according to a function that measures, for each pixel, occurrence of a desired characteristic, other than luminance alone, in the input images at each pixel location to provide a single value for each output pixel in the single channel image from a range of values that represent a likelihood of the occurrence of the desired characteristic;

computing an estimate of motion of the desired characteristic between the two input images based on the single channel images generated for the two input images; and

processing at least one of the two input images to generate an output image that includes a motion-based effect, wherein the processing uses the computed estimate of motion of the desired characteristic.

2. The method of claim 1, wherein the desired characteristic is edge magnitude.

3. The method of claim 1, wherein the desired characteristic is proximity to a color;

and the function measures the proximity to a color of a region around each pixel location.

4. The method of claim 1, wherein performing the motion-based effect includes generating several images from the two input images according to an interpolation of the computed estimate of motion over time between the two images.

5. The method of claim 4, wherein the desired characteristic is edge magnitude.

6. The method of claim 4, wherein:

the desired characteristic is proximity to a color; and

the function measures the proximity to a color of a region around each pixel location.

13. The method of claim 1, wherein computing the estimate of motion uses a gradient-based method that uses the single channel images generated for the two input images and a constraint that a total of the desired characteristic is constant from one image to a next image, and wherein the gradient-based method comprises computing optical flow for the single channel images.

15. The method of claim 13, wherein the gradient-based method comprises computing, for each pixel in an image, a vector that describes the motion for the pixel from one image to the next.

17. The method of claim 13, wherein the gradient-based method comprises using an optical flow constraint equation.

7. An apparatus for applying a motion effect using two input images, comprising;

a processor system; and

a memory storing code which, when executed on the processor system causes the apparatus to;

generate a single channel image for each of two input images according to a function that measures, for each pixel, occurrence of a desired characteristic, other than luminance alone, in the input images at each pixel location to provide a single value for each output pixel in the single channel image from a range of values that represent a likelihood of the occurrence of the desired characteristic;

compute an estimate of motion of the desired characteristic between the two images using the single channel images generated for the two input images; and

process at least one of the two input images to generate an output image that includes a motion-based effect, wherein the processing uses the computed estimate of motion of the desired characteristic.

8. The apparatus of claim 7, wherein the desired characteristic is edge magnitude.

9. The apparatus of claim 7, wherein the desired characteristic is proximity to a color.

10. The apparatus of claim 7, wherein the means for performing generating a motion-based effect includes means for generating several images from the two input images according to an interpolation of the computed estimate of motion over time between the two images.

11. The apparatus of claim 10, wherein the desired characteristic is edge magnitude.

12. The apparatus of claim 10, wherein;

the desired characteristic is proximity to a color; and

generating the single channel image involves measuring the proximity to a color of a region wound each pixel location.

14. The apparatus of claim 7, wherein the estimate of motion uses a gradient-based method that uses the single channel images generated for the two input images and a constraint that a total of the desired characteristic is constant from one image to a next image, and wherein the gradient-based method includes computing optical flow for the single channel images.

16. The apparatus of claim 14, wherein the estimate of motion using a gradient-based method comprises computing, for each pixel in an image, a vector that describes the motion for the pixel from one image to the next.

18. The apparatus of claim 14, wherein the estimate of motion using a gradient-based method comprises using an optical flow constraint equation.