US 12,094,247 B2
Expression recognition method and related apparatus
Xing Ji, Shenzhen (CN); Yitong Wang, Shenzhen (CN); and Zheng Zhou, Shenzhen (CN)
Assigned to TENCENT TECHNOLOGY (SHENZHEN) COMPANY LIMITED, Shenzhen (CN)
Filed by Tencent Technology (Shenzhen) Company Limited, Shenzhen (CN)
Filed on May 17, 2021, as Appl. No. 17/322,710.
Application 17/322,710 is a continuation of application No. PCT/CN2020/078579, filed on Mar. 10, 2020.
Claims priority of application No. 201910194881.8 (CN), filed on Mar. 14, 2019.
Prior Publication US 2021/0271862 A1, Sep. 2, 2021
Int. Cl. G06K 9/00 (2022.01); G06F 18/214 (2023.01); G06N 3/08 (2023.01); G06V 10/44 (2022.01); G06V 10/75 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/16 (2022.01)
CPC G06V 40/176 (2022.01) [G06F 18/214 (2023.01); G06N 3/08 (2013.01); G06V 10/454 (2022.01); G06V 10/751 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/171 (2022.01); G06V 40/172 (2022.01)] 20 Claims
OG exemplary drawing
 
1. An expression recognition method performed by an electronic device having one or more processors and memory, the method comprising:
obtaining an image that includes a face, wherein the face includes a plurality of facial action units, a displacement of each facial action unit from its default position indicating an extent of a facial expression associated with the facial action unit;
performing feature extraction on the image, to obtain global facial expression information corresponding to the face and local facial feature information corresponding to the face, wherein the local facial feature information indicates an extent of the displacement by a corresponding facial action unit in the face;
determining a global facial emotion probability value according to the global facial expression information;
determining a local facial feature expression probability value according to the local facial feature information of the corresponding facial action unit in the face; and
selecting, among a plurality of candidate facial emotions and a plurality of candidate facial expressions, a target facial emotion and a target facial expression corresponding to the target facial emotion for the face in the image according to the global facial emotion probability value and the local facial feature expression probability value.