System and method for measuring image similarity based on semantic meaning
First Claim
1. A computer implemented method for characterizing images and determining image similarity based on semantic meaning of images, comprising:
- deriving a plurality of semantic categories for representing important semantic cues in images, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories;
for each semantic category, forming a set of the perceptual features comprising required features and frequently occurring features;
comparing an image to said semantic categories; and
classifying said image as belonging to one of said semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in said image.
2 Assignments
0 Petitions
Accused Products
Abstract
A method includes deriving a plurality of semantic categories for representing important semantic cues in images, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories; for each semantic category, forming a set of the perceptual features comprising required features and frequently occurring features; comparing an image to said semantic categories; and classifying said image as belonging to one of said semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in said image. A database contains image information, where the image information includes at least one of already classified images, network locations of already classified images and documents containing already classified images. The database is searched for images matching an input query, comprising, e.g., an image, text, or both.
251 Citations
60 Claims
-
1. A computer implemented method for characterizing images and determining image similarity based on semantic meaning of images, comprising:
-
deriving a plurality of semantic categories for representing important semantic cues in images, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories; for each semantic category, forming a set of the perceptual features comprising required features and frequently occurring features; comparing an image to said semantic categories; and classifying said image as belonging to one of said semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in said image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 47)
-
-
22. A data processing system comprising a data processor, a graphical user interface and a memory that stores a database containing image information, where the image information comprises at least one of already classified images, network locations of already classified images and documents containing already classified images, said data processor operating in accordance with a stored program for classifying images by deriving a plurality of semantic categories for representing important semantic cues in images, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories;
- said data processor, for each semantic category, forming a set of the perceptual features comprising required features and frequently occurring features;
comparing an image to said semantic categories; and
classifying said image as belonging to one of said semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in said image, said data processor storing image-related classification data in said database. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 48)
- said data processor, for each semantic category, forming a set of the perceptual features comprising required features and frequently occurring features;
- 43. A computer program embodied on a computer readable media for directing a computer to execute a method for processing digitally represented images, comprising program instructions for classifying images by deriving a plurality of semantic categories for representing important semantic cues in images, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories, where for each semantic category said program instructions form a set of the perceptual features comprising required features and frequently occurring features, compares an image to said semantic categories and classifies said image as belonging to one of said semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in said image.
-
49. A computer implemented method for characterizing images and determining image similarity based on semantic meaning of images, comprising:
-
for each semantic category of a plurality of semantic categories, forming a set of perceptual features comprising required features and frequently occurring features, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories; determining features of an image; comparing features of the image to the sets of perceptual features of the semantic categories; and classifying the image as belonging to one of the semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in the features of the image. - View Dependent Claims (50, 51)
-
-
52. An apparatus comprising:
-
means for forming, for each semantic category of a plurality of semantic categories, a set of perceptual features comprising required features and frequently occurring features, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories; means for determining features of an image; means for comparing features of the image to the sets of perceptual features of the semantic categories; and means for classifying the image as belonging to one of the semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in the features of the image. - View Dependent Claims (53, 54)
-
- 55. A data processing system comprising a data processor and at least one memory comprising a stored program, the data processor operating in accordance with the stored program to form, for each semantic category of a plurality of semantic categories, a set of perceptual features comprising required features and frequently occurring features, where each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories, said data processor operating in accordance with the stored program to determine features of an image, to compare features of the image to the sets of perceptual features of the semantic categories, and to classify the image as belonging to one of the semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in the features of the image.
-
59. A computer implemented method for characterizing images and determining image similarity based on semantic meaning of images, comprising:
-
performing subjective experiments with human observers to determine perceptual features of a plurality of images and to determine sets of semantic categories for the plurality of images, wherein each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories; for each semantic category of a plurality of semantic categories, forming a set of perceptual features comprising required features and frequently occurring features; determining features of a query image; classifying the query image as belonging to one of the semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in the features of the image, wherein classifying further comprises computing a similarity measure between the perceptual features used to describe a semantic category and corresponding features determined from the query image; and assigning the query image to that semantic category that corresponds to a highest value of the similarity measure.
-
-
60. A computer implemented method for characterizing images and determining image similarity based on semantic meaning of images, comprising:
-
performing subjective experiments with human observers to determine perceptual features of a plurality of images and to determine sets of semantic categories for the plurality of images, wherein each semantic category is modeled through a combination of perceptual features that define the semantics of that category and that discriminate that category from other categories; for each semantic category of a plurality of semantic categories, forming a set of perceptual features comprising required features and frequently occurring features; determining features of a query image; classifying the query image as belonging to one of the semantic categories if all of the required features and at least one of the frequently occurring features for that semantic category are present in the features of the image, wherein classifying further comprises computing a similarity measure between the perceptual features used to describe a semantic category and corresponding features determined from the query image, where the similarity measure comprises;
-
Specification