ROBUST KEYPOINT FEATURE SELECTION FOR VISUAL SEARCH WITH SELF MATCHING SCORE

摘要

To improve feature selection accuracy during a visual search, interest points within a query image are two-way matched to features in an affine transformed image or otherwise transformed version of the query image. A user device implements a method for selecting local descriptors in the visual search. The method includes: detecting a first set of interest points for the original image; computing an affine transform matrix; computing a new image as a transformation of the original image using the affine transform matrix; detecting a second set of interest points from the and new image; performing a two-way matching between the first set of interest points and the second set of interest points; sorting matching pairs according to a specified self-matching score (SMS); assigning an infinite value to SMS of unmatched interest points from the original image; selecting the interest points based on SMS. Significant performance gains reduce false positive matches.

主权项

1. A method, comprising:
detecting a first set of key points for an original image to be used as a query image for the visual search request; generating a affine-transformed image as an affine-transformation of the original image; detecting a second set of key points from the transformed image; determining matches between key points for the original image and key points for the transformed image; and selecting matching key points for the original and transformed images to transmit to the visual search server in the visual search request.