US 12,236,711 B2
Apparatus and method for providing missing child search service based on face recognition using deep-learning
Min-Sik Kim, Sejong (KR)
Assigned to OneMoreSecurity Inc., Sejong (KR)
Appl. No. 17/606,590
Filed by OneMoreSecurity Inc., Sejong (KR)
PCT Filed Aug. 10, 2021, PCT No. PCT/KR2021/010589
§ 371(c)(1), (2) Date Oct. 26, 2021,
PCT Pub. No. WO2022/035190, PCT Pub. Date Feb. 17, 2022.
Claims priority of application No. 10-2020-0100700 (KR), filed on Aug. 11, 2020; application No. 10-2020-0127867 (KR), filed on Oct. 5, 2020; and application No. 10-2021-0022739 (KR), filed on Feb. 19, 2021.
Prior Publication US 2022/0319232 A1, Oct. 6, 2022
Int. Cl. G06V 40/16 (2022.01); G06Q 50/22 (2024.01); G06Q 50/26 (2024.01); G06T 7/246 (2017.01); G06V 20/52 (2022.01); G06V 40/50 (2022.01)
CPC G06V 40/172 (2022.01) [G06Q 50/22 (2013.01); G06Q 50/265 (2013.01); G06T 7/246 (2017.01); G06V 20/52 (2022.01); G06V 40/161 (2022.01); G06V 40/50 (2022.01); G06T 2207/30201 (2013.01); G06T 2207/30232 (2013.01)] 12 Claims
OG exemplary drawing
 
1. A method for providing a missing child search service based on face recognition using deep learning, the method comprising:
registering missing child occurrence information including a first missing child image and information about a location from which and a time at which a child went missing when occurrence of a missing child is reported by at least one first user terminal;
registering missing child finding information including a second missing child image and information about a location and a time at which a missing child was found when finding of the missing child is reported by at least one second user terminal;
calculating a similarity between pieces of facial feature information extracted from the first missing child image and the second missing child image, respectively, based on deep learning; and
when the similarity is equal to or greater than a predetermined threshold value, delivering contact information of the second user terminal and the missing child finding information to the first user terminal, and delivering contact information of the first user terminal and the missing child occurrence information to the second user terminal,
wherein the facial feature information is acquired by:
detecting a face area from each of the first missing child image and the second missing child image;
detecting feature points of a face from the detected face area through a three- dimensional (3D) model estimation scheme;
normalizing the face area based on the detected feature points; and
calculating a feature vector based on a convolutional neural network from the normalized face area.