Statistical bigram correlation model for image retrieval
First Claim
1. A computer-implemented method for image retrieval using a statistical bigram correlation model, the method comprising:
- receiving a plurality of images responsive to multiple search sessions;
determining whether the images are semantically relevant images via relevance feedback; and
estimating a respective semantic correlation between each of at least one pair of the images with a respective bigram frequency, each respective bigram frequency being based on multiple search sessions in which each image of the pair is indicated to be a semantically relevant image.
1 Assignment
0 Petitions
Accused Products
Abstract
The disclosed subject matter improves iterative results of content-based image retrieval (CBIR) using a bigram model to correlate relevance feedback. Specifically, multiple images are received responsive to multiple image search sessions. Relevance feedback is used to determine whether the received images are semantically relevant. A respective semantic correlation between each of at least one pair of the images is then estimated using respective bigram frequencies. The bigram frequencies are based on multiple search sessions in which each image of a pair of images is semantically relevant.
-
Citations
20 Claims
-
1. A computer-implemented method for image retrieval using a statistical bigram correlation model, the method comprising:
-
receiving a plurality of images responsive to multiple search sessions;
determining whether the images are semantically relevant images via relevance feedback; and
estimating a respective semantic correlation between each of at least one pair of the images with a respective bigram frequency, each respective bigram frequency being based on multiple search sessions in which each image of the pair is indicated to be a semantically relevant image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
-
-
15. A computer-readable medium for image retrieval using a statistical bigram correlation model, the computer-readable medium comprising computer-executable instructions for:
-
receiving a plurality of images responsive to multiple search sessions;
determining whether the images are semantically relevant images via relevance feedback; and
estimating a respective semantic correlation between each of at least one pair of the images with a respective bigram frequency, each respective bigram frequency representing a probability of whether two of the images are semantically related to one-another based on a co-occurrence frequency that each image of the two images was relevant in a previous query/feedback session. - View Dependent Claims (16, 17, 18)
-
-
19. A computing device for image retrieval using a statistical bigram correlation model, the computing device comprising:
-
a processor; and
a memory coupled to the processor, the memory comprising computer-executable instructions that are fetched and executed by the processor for;
receiving a plurality of images responsive to multiple search sessions;
determining whether the images are semantically relevant images via relevance feedback; and
estimating a respective semantic correlation between each of at least one pair of the images with a respective bigram frequency, each respective bigram frequency being based on multiple search sessions in which each image of the pair is indicated to be a semantically relevant image. - View Dependent Claims (20)
-
Specification