Acceleration of linear classifiers
First Claim
Patent Images
1. A method comprising:
- receiving a plurality of training feature vectors indicative of an image;
normalizing the plurality of training feature vectors to a uniform length;
defining a matching space including the plurality of training feature vectors, wherein the matching space determines whether an input image feature vector is a match;
storing the matching space; and
determining whether an input image feature vector falls within the matching space based on a range query.
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Abstract
In one embodiment, image detection is improved or accelerated using an approximate range query to classify images. A controller is trained on a set of training feature vectors. The training feature vectors represent an image. The feature vectors are normalized to a uniform length. The controller defines a matching space that includes the set of training feature vectors. The controller is configured to identify whether an input vector for a tested image falls within the matching space based on a range query. When the input vector falls within the matching space, the tested image substantially matches the portion of the image used to train the controller.
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Citations
18 Claims
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1. A method comprising:
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receiving a plurality of training feature vectors indicative of an image; normalizing the plurality of training feature vectors to a uniform length; defining a matching space including the plurality of training feature vectors, wherein the matching space determines whether an input image feature vector is a match; storing the matching space; and determining whether an input image feature vector falls within the matching space based on a range query. - View Dependent Claims (18)
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2. A method comprising:
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receiving a plurality of training feature vectors indicative of an image; normalizing the plurality of training feature vectors to a uniform length; defining a matching space including the plurality of training feature vectors, wherein the matching space determines whether an input image feature vector is a match; storing the matching space; calculating a range query distance; and determining whether an input image feature vector falls within the matching space based on the range query distance and a query vector. - View Dependent Claims (3, 4, 5, 6, 7, 8)
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9. A non-transitory computer readable medium including instructions that when executed are operable to:
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receiving feature vectors having a uniform length; receiving a plurality of input feature vectors; receiving a plurality of linear classifiers; and performing an approximate range query, for each of the plurality of linear classifiers, to identify a subset of input feature vectors, wherein each of the plurality of linear classifiers is defined by a query vector and a query radius. - View Dependent Claims (10)
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11. An apparatus comprising:
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at least one processor; and at least one memory including computer program code for one or more programs;
the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least perform;receive a plurality of training feature vectors indicative of an image; normalize the plurality of training feature vectors to a uniform length; define a matching space including the plurality of training feature vectors, wherein the matching space determines whether an input image feature vector is a match; and store the matching space; and calculate a range query distance as a function of a decision threshold. - View Dependent Claims (12, 13, 14, 15, 16, 17)
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Specification