RenQiang / 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
☆21Updated 10 years ago
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