Query optimization for visual information retrieval system
First Claim
1. A method of optimization of object comparisons for a database query, wherein the database includes a plurality of visual objects and associated feature vectors, the method comprising:
- providing a cost for executing a comparison process for each of a plurality of visual primitives of any one of the feature vectors; and
applying the comparison process for each visual primitive as between any selected at least two of the feature vectors as a function of the cost.
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Abstract
A system and method for content-based search and retrieval of visual objects. A base visual information retrieval (VIR) engine utilizes a set of universal primitives to operate on the visual objects. An extensible VIR engine allows custom, modular primitives to be defined and registered. A custom primitive addresses domain specific problems and can utilize any image understanding technique. Object attributes can be extracted over the entire image or over only a portion of the object. A schema is defined as a specific collection of primitives. A specific schema implies a specific set of visual features to be processed and a corresponding feature vector to be used for content-based similarity scoring. A primitive registration interface registers custom primitives and facilitates storing of an analysis function and a comparison function to a schema table. A heterogeneous comparison allows objects analyzed by different schemas to be compared if at least one primitive is in common between the schemas. A threshold-based comparison is utilized to improve performance of the VIR engine. A distance between two feature vectors is computed in any of the comparison processes so as to generate a similarity score.
259 Citations
16 Claims
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1. A method of optimization of object comparisons for a database query, wherein the database includes a plurality of visual objects and associated feature vectors, the method comprising:
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providing a cost for executing a comparison process for each of a plurality of visual primitives of any one of the feature vectors; and applying the comparison process for each visual primitive as between any selected at least two of the feature vectors as a function of the cost. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. A similarity engine for content-based retrieval of images having the capability of optimizing object comparisons for a database query wherein the database includes a plurality of visual objects and associated feature vectors, the engine comprising:
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means for providing a cost for executing a comparison process for each of a plurality of visual primitives of any one of the feature vectors; and means for employing the comparison process for each visual primitive as between any selected at least two of the feature vectors as a function of the cost.
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- 10. The engine of claim 10, wherein the means for applying orders the visual primitives from least to greatest cost.
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12. A method of optimization of object comparisons for a database query utilizing visual primitives each of which includes a comparison function and wherein the database includes a plurality of visual objects, the method comprising:
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determining a cost for executing a comparison function for each of a plurality of visual primitives belonging to a feature vector representative of a visual object; and applying the comparison process for each visual primitive as between any selected at least two of the feature vectors as a function of the cost. - View Dependent Claims (13, 14, 15, 16)
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Specification