Method and apparatus for processing data

• US 20030108242A1
• Filed: 12/08/2001
• Published: 06/12/2003
• Est. Priority Date: 12/08/2001
• Status: Abandoned Application

• Current Assignee: Stephen W. Conant
• Original Assignee: Stephen W. Conant
• Inventors: Conant, Stephen W.
• Application Number:
  US10/015,931
• Publication Number:
  US 20030108242A1
• Time in Patent Office: Days
• US Class Current: 382/190
• CPC Class Codes: G06V 10/443 by matching or filtering
• CPC Class Codes: G06V 30/1988 Graph matching graphical image representation G06V30/18181

Abstract

The invention discloses a method for detecting points of interest in image samples that have a high probability of being present with a consistent spatial relationship to one another, and with high visual similarity, in different images. Some embodiments of the invention exhaustively sample the images, and generate a set of basis functions to capture image components. Each sample is encoded through a set of coefficients produced using the basis functions. Encoding coefficients are then used in a numerical analysis to determine their relative likelihood of representing image locations similar to image locations in other images that containing a common object, symbol or character with a similar viewpoint and scale. The invention proposes a method for identifying identical objects, such as image objects, symbols and characters with differences of object rotation and scaling, differences in lighting and possible foreground occlusion.

Claims

1. A method for constructing an interest point detector comprising:

obtaining a set of encoding functions describing a plurality of data samples of a data set;

obtaining a set of encoding factors associated with said set of encoding functions;

obtaining a plurality of numerical descriptors associated with said plurality of data samples by analyzing said set of encoding factors using a threshold criterion; and

obtaining a subset of numerical descriptors from said plurality of numerical descriptors by analyzing said plurality of numerical descriptors.

2. The method of claim 1 wherein said data samples further comprise image data samples.

3. The method of claim 1 wherein said set of encoding functions further comprises a set of basis functions.

4. The method of claim 1 wherein said step of obtaining a set of encoding factors further comprises computing a set of encoding coefficients.

5. The method of claim 1 wherein said step of obtaining a subset of numerical descriptors further comprises obtaining range criteria for selecting said subset of numerical descriptors from said plurality of numerical descriptors.

6. A method for processing image data comprising:

obtaining image data for at least one image;

obtaining a plurality image samples from said image data;

producing a set of encoding functions for said at least one image;

extracting a set of encoding factors associated with said set of encoding functions for each one of said plurality of image samples;

obtaining a plurality of target images by concatenating two sets or more of said set of encoding factors;

obtaining a set of of numerical descriptors using said set of encoding factors for each one of said plurality of target images; and

obtaining an image object detector using said plurality of numerical descriptors from said at least one image.

7. The method in claim 6 wherein said step of obtaining image data for at least one image further comprises obtaining digitized image data.

8. The method in claim 6 wherein said step of obtaining image data for at least one image further comprises convolving said image data with a numerical filter.

9. The method in claim 6 wherein said plurality of image samples further comprises adjacent image areas.

10. The method in claim 6 wherein said plurality of image samples further comprises a plurality of overlapping image areas.

11. The method in claim 6 wherein said plurality of image samples further comprises a plurality of non-overlapping image areas.

12. The method of claim 6 wherein said step of producing a set of encoding functions further comprises producing a set of basis functions.

13. The method of claim 6 wherein said step of producing a set of encoding functions further comprises producing an overcomplete set of encoding functions.

14. The method of claim 6 wherein said plurality of encoding factors further comprises a plurality of encoding coefficients.

15. The method of claim 14 wherein said plurality of encoding coefficients further comprises a plurality of coefficients having a sparse distribution.

16. The method of claim 6 wherein said step of obtaining a plurality of numerical distributions further comprises computing a standard deviation threshold.

17. The method of claim 6 wherein said step of obtaining a plurality of numerical distributions further comprises computing a set of boundaries for selecting from said plurality of numerical descriptors.

18. The method of claim 6 wherein said step of obtaining an image object detector further comprises using an association graph.

19. The method of claim 6 wherein said step of obtaining an image object detector further comprises measuring a similarity value between a plurality of point pairs from said at least one image.

20. The method of claim 6 wherein said step of obtaining an image object detector further comprises locating groups of target image pairs having a highest valued maximal clique.