Scalable Recognition With A Vocabulary Tree

 Designed a recognition scheme, scaling efficiently to a great number of objects: extracted SIFT features for each image, and arranged these descriptors by a vocabulary tree, clustering by k-means at each level  Established a database with 1259 images, achieved an accuracy of 89.6% and average used time 3.2s