US 11,954,145 B2
Methods, systems, and media for image searching
Varshanth Ravindra Rao, North York (CA); Md Ibrahim Khalil, Toronto (CA); Peng Dai, Markham (CA); and Juwei Lu, North York (CA)
Assigned to HUAWEI TECHNOLOGIES CO., LTD., Shenzhen (CN)
Filed by HUAWEI TECHNOLOGIES CO., LTD., Gangdong (CN)
Filed on Jun. 22, 2021, as Appl. No. 17/354,786.
Prior Publication US 2022/0405322 A1, Dec. 22, 2022
Int. Cl. G06F 16/53 (2019.01); G06F 16/51 (2019.01); G06F 16/55 (2019.01); G06F 16/583 (2019.01); G06V 10/74 (2022.01)
CPC G06F 16/55 (2019.01) [G06F 16/51 (2019.01); G06F 16/53 (2019.01); G06F 16/583 (2019.01); G06V 10/74 (2022.01)] 15 Claims
OG exemplary drawing
 
1. A method for image searching for images comprising at least one query image and a plurality of candidate images by ranking the plurality of candidate images based on similarity to the at least one query image, the method comprising:
determining, for each candidate image of the plurality of candidate images, a first model similarity measure from an output of a first model configured for scene classification to perceive scenes in the images, wherein the first model similarity measure is measured between each candidate image and the at least one query image;
determining, for each candidate image of the plurality of candidate images, a second model similarity measure from the output of a second model configured for attribute classification to perceive attributes in the images, wherein the second model similarity measure is measured between each candidate image and the at least one query image;
obtaining, for each candidate image of the plurality of candidate images, a similarity agglomerate index of a weighted aggregate of the first model similarity measure and the second model similarity measure;
ranking the plurality of candidate images based on the respective similarity agglomerate index of each candidate image and generating a first ranked candidate images corresponding to the searched images;
determining, for each candidate image of a subset of the first ranked candidate images, a third model similarity measure from the output of a third model configured for object detection, wherein the third model similarity measure is measured between each candidate image of the subset of the first ranked candidate images and the at least one query image;
ranking the subset of the first ranked candidate images based on the respective third model similarity measure of each candidate image of the subset of the first ranked candidate images and generating a second ranked candidate images corresponding to the searched images;
determining, for each candidate image of a subset of the second ranked candidate images, a fourth model similarity measure from the output of a fourth model configured for computing image statistics, wherein the fourth model similarity measure is measured between each candidate image of the subset of the second ranked candidate images and the at least one query image; and
ranking the subset of the second ranked candidate images based on the respective fourth model similarity measure and generating a final ranked candidate images corresponding to the searched images.