Abstract
We propose GIFTS (Goods Image Feature for Tree Search) local image feature for large scale object recognition system. GIFTS is a sort of keypoint feature and its feature vector consists of intensity delta of selected 128 pixel pairs around the keypoint. By generating KD-Tree from GIFTS feature vectors of training images and using the KD-Tree for searching nearest neighbor feature vectors of query image, order of log N query time for the specific object recognition is attained. We apply the proposed method to the query of book covers among 100 thousand training images of books, and performed over 99% recognition accuracy in the query time within one second.
