MATLAB File Help: cv.BOWKMeansTrainer Index
cv.BOWKMeansTrainer

kmeans-based class to train visual vocabulary using the bag of visual words approach

kmeans-based class for training the bag of visual words vocabulary from a set of descriptors.

Example

% create bag of visual words
trainer = cv.BOWKMeansTrainer(K);
dictionary = trainer.cluster(train_descs);

% Compute histogram of visual word occurrences of an image
extractor = cv.BOWImgDescriptorExtractor('SIFT','BruteForce');
extractor.setVocabulary(dictionary);
descs = extractor.compute(im, keypoints);

References

"Visual Categorization with Bags of Keypoints" by Gabriella Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cedric Bray, 2004.

See also
cv.BOWKMeansTrainer/BOWKMeansTrainer, cv.BOWImgDescriptorExtractor, bagOfFeatures
Class Details
Superclasses handle
Sealed false
Construct on load false
Constructor Summary
BOWKMeansTrainer The constructor 
Property Summary
id Object ID 
Method Summary
  add Adds descriptors to a training set 
  addlistener Add listener for event. 
  clear Clear training descriptors 
  cluster Clusters train descriptors 
  delete Destructor 
  descriptorsCount Returns the count of all descriptors stored in the training set 
  eq == (EQ) Test handle equality. 
  findobj Find objects matching specified conditions. 
  findprop Find property of MATLAB handle object. 
  ge >= (GE) Greater than or equal relation for handles. 
  getDescriptors Returns a training set of descriptors 
  gt > (GT) Greater than relation for handles. 
Sealed   isvalid Test handle validity. 
  le <= (LE) Less than or equal relation for handles. 
  lt < (LT) Less than relation for handles. 
  ne ~= (NE) Not equal relation for handles. 
  notify Notify listeners of event.