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US 9,436,890 B2Granted
Method of generating feature vector, generating histogram, and learning classifier for recognition of behavior
AssigneeSamsung Electronics Co., Ltd.
InventorsWon Jun Kim, Byung In Yoo, Jae Joon Han
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Abstract
Example embodiments disclose a method of generating a feature vector, a method of generating a histogram, a learning unit classifier, a recognition apparatus, and a detection apparatus, in which a feature point is detected from an input image based on a dominant direction analysis of a gradient distribution, and a feature vector corresponding to the detected feature point is generated.
Claims42
A method of generating a feature vector, the method comprising:
- detecting a feature point from an input image based on a dominant direction of a gradient distribution in the input image, the detecting including,
- detecting a pixel corresponding to a window having a contrast of coherence in a dominant direction;
- and
- generating a feature vector corresponding to the feature point.
1 more element
A method of image processing, the method comprising:
- detecting a plurality of feature points comprised in an input image based on a dominant direction of a gradient distribution in the input image;
- generating a plurality of feature vectors corresponding to the plurality of feature points, the generating including
- accumulating a strength of coherence in the dominant direction within a local region corresponding to the plurality of feature points in order to generate the plurality of feature vectors;
- and
- mapping the plurality of feature vectors to codewords in a codebook, to generate a histogram corresponding to the input image based on the mapped feature vectors.
2 more elements
An apparatus for learning a classifier, the apparatus comprising:
- a detector configured to detect a plurality of feature points comprised in a plurality of training images based on a dominant direction analysis of a gradient distribution, wherein the detector is configured to detect pixels corresponding to windows having a contrast of coherence in a dominant direction to be the plurality of feature points;
- a generator configured to generate a plurality of feature vectors corresponding to the plurality of feature points;
- a mapper configured to map the plurality of feature vectors to codewords comprised in a given codebook, and generate a histogram corresponding to the plurality of training images;
- and
- a learning unit configured to learn a classifier based on the histogram.
2 more elements
A recognition apparatus, the apparatus comprising:
- a detector configured to detect a plurality of feature points in an input image based on a dominant direction analysis of a gradient distribution;
- a generator configured to generate a plurality of feature vectors corresponding to the plurality of feature points, wherein the generator is configured to accumulate a strength of coherence in a dominant direction of a local region corresponding to the plurality of feature points in order to generate the plurality of feature vectors;
- a mapper configured to map the plurality of feature vectors in a given codebook, and generate a histogram corresponding to the input image;
- and
- a recognizer configured to recognize content of the input image based on a learned parameter and the histogram.
2 more elements
A detection apparatus, the apparatus comprising:
- a feature point detector configured to detect a plurality of feature points comprised in at least a portion of an input image based on a dominant direction analysis of a gradient distribution, wherein the feature point detector is configured to detect pixels corresponding to window having a contrast of coherence in a dominant direction to be the plurality of feature points;
- a generator configured to generate a plurality of feature vectors corresponding to the plurality of feature points;
- a mapper configured to map the plurality of feature vectors to codewords comprised in a given codebook, and generate a histogram corresponding to the at least one portion;
- and
- a region detector configured to compare a reference histogram to the histogram, and detect a region corresponding to the reference histogram.
2 more elements
Dependencies are inferred from the claim text.