A METHOD OF PROVIDING A FEATURE DESCRIPTOR FOR DESCRIBING AT LEAST ONE FEATURE OF AN OBJECT REPRESENTATION
First Claim
1. A method of providing a feature descriptor for describing at least one feature of an object representation, comprising the steps of:
- a) providing an original feature descriptor comprising at least one vector or a plurality of K vectors having equal sum of vector entry values and each vector having H entries;
b) projecting each vector on a lower dimensional space of size H−
1 or lower to gain a projected feature descriptor comprising projected vectors of H−
1 entries or lower, such that it is possible to obtain a similarity measure between two projected feature descriptors equal to the similarity measure between the two corresponding original feature descriptors; and
c) providing the projected feature descriptor as a lossless compressed feature descriptor.
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Accused Products
Abstract
A method of providing a feature descriptor for describing at least one feature of an object representation includes the steps of providing an original feature descriptor comprising at least one vector or a plurality of K vectors having equal sum of vector entry values and each vector having H entries, projecting each vector on a lower dimensional space of size H-1 or lower to gain a projected feature descriptor comprising projected vectors of H-1 entries or lower, such that it is possible to obtain a similarity measure between two projected feature descriptors equal to the similarity measure between the two corresponding original feature descriptors, and providing the projected feature descriptor as a lossless compressed feature descriptor.
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Citations
29 Claims
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1. A method of providing a feature descriptor for describing at least one feature of an object representation, comprising the steps of:
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a) providing an original feature descriptor comprising at least one vector or a plurality of K vectors having equal sum of vector entry values and each vector having H entries; b) projecting each vector on a lower dimensional space of size H−
1 or lower to gain a projected feature descriptor comprising projected vectors of H−
1 entries or lower, such that it is possible to obtain a similarity measure between two projected feature descriptors equal to the similarity measure between the two corresponding original feature descriptors; andc) providing the projected feature descriptor as a lossless compressed feature descriptor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14)
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15-19. -19. (canceled)
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20. A method of matching at least one feature of an object representation, comprising:
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extracting at least one current feature from an object representation and providing at least one current feature descriptor for the extracted current feature; providing a plurality of feature descriptors, wherein each feature descriptor is configured to be used in matching, at least one feature of an object representation, wherein the feature descriptor is describing at least one feature extruded from an object representation and is indicative of a selected region of interest around the extracted feature, which region is divided into sub-regions, and which feature descriptor includes; a feature descriptor vector containing information about at least one vector or a plurality of K vectors with concatenation of the vectors of the sub-regions, with at least one respective vector for every sub-region; and wherein the feature descriptor vector comprises vectors projected onto a lower dimensional space of (H−
1) or lower from a corresponding vector of H entries of an original feature descriptor; andcomparing a first of the plurality of the feature descriptors with at least one of the other feature descriptors for matching the at least one current feature. - View Dependent Claims (21, 22, 26, 27, 28, 29)
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23-24. -24. (canceled)
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25. A non-transitory computer readable medium comprising software code sections adapted to perform a method for providing a feature descriptor for describing at least one feature of an object representation, comprising:
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a) providing an original feature descriptor comprising at least one vector or a plurality of K vectors having equal sum of vector entity values and each vector having H entries. b) projecting each vector on a lower dimensional space of size H−
1 or lower to gain a projected feature descriptor comprising projected vectors of H−
1 entries or lower, such that it is possible to obtain a similarity measure between two projected feature descriptors equal to the similarity measure between the two corresponding original feature descriptors; andc) providing the projected feature descriptor as a lossless compressed feature descriptor.
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Specification