US 11,947,631 B2
Reverse image search based on deep neural network (DNN) model and image-feature detection model
Jong Hwa Lee, San Diego, CA (US); and Praggya Garg, Rancho Santa Fe, CA (US)
Assigned to SONY GROUP CORPORATION, Tokyo (JP)
Filed by SONY GROUP CORPORATION, Tokyo (JP)
Filed on Sep. 22, 2021, as Appl. No. 17/482,290.
Claims priority of provisional application 63/189,956, filed on May 18, 2021.
Prior Publication US 2022/0374647 A1, Nov. 24, 2022
Int. Cl. G06K 9/00 (2022.01); G06F 3/14 (2006.01); G06F 18/22 (2023.01); G06F 18/2431 (2023.01); G06F 18/25 (2023.01); G06F 18/40 (2023.01); G06N 3/04 (2023.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G06V 10/40 (2022.01); G06V 20/40 (2022.01)
CPC G06F 18/22 (2023.01) [G06F 3/14 (2013.01); G06F 18/2431 (2023.01); G06F 18/253 (2023.01); G06F 18/40 (2023.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/0002 (2013.01); G06V 10/40 (2022.01); G06V 20/46 (2022.01); G06T 2207/10016 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30168 (2013.01)] 20 Claims
OG exemplary drawing
 
1. An electronic device, comprising:
circuitry configured to:
receive a first image;
extract, by a Deep Neural Network (DNN) model, a first set of image features associated with the received first image;
generate a first feature vector associated with the received first image based on the extracted first set of image features;
extract, by an image-feature detection model, a second set of image features associated with the received first image;
generate a second feature vector associated with the received first image based on the extracted second set of image features;
determine, based on a resolution of the received first image, each of:
a first weight associated with the generated first feature vector, and
a second weight associated with the generated second feature vector;
combine the generated first feature vector and the generated second feature vector based on the determined first weight and the determined second weight;
generate a third feature vector associated with the received first image based on the combination of the generated first feature vector and the generated second feature vector;
determine a similarity metric between the generated third feature vector associated with the received first image and a fourth feature vector of each of a set of pre-stored second images;
identify a pre-stored third image from the set of pre-stored second images based on the determined similarity metric; and
control a display device to display information associated with the identified pre-stored third image.