opencv - Image detection features: SIFT, HISTOGRAM and EGDE -
i working on developing object classifier using 3 different features i.e sift, histogram , egde. however these 3 features have different dimensional vector e.g. sift = 128 dimension. hist = 256. now these features cannot concatenated once vector due different sizes. planning not sure if going correct way this: for each features train classifier separately , apply classification separately 3 different features , count majority , declare image majority votes. do think correct way? there several ways classification results take account multiple features. have suggested 1 possibility instead of combining features train multiple classifiers , through protocol, arrive @ consensus between them. typically under field of ensemble methods . try googling boosting, random forests more details on how combine classifiers. however, not true feature vectors cannot concatenated because have different dimensions. can still concatenate features huge vector. e.g., joining sift , hi...
