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公开(公告)号：US20240065595A1
公开(公告)日：2024-02-29
申请号：US18387062
申请日：2023-11-06
Applicant: Beijing University Of Technology
Inventor： Mi LI , Bin HU , Shengfu LV , Jiaming KANG , Wei ZHANG
CPC classification number: A61B5/163 , A61B5/7264 , A61B5/7278
Abstract: A method and system for calculating emotional indicators based on pupil-wave are provided. The operation of calculating emotional indicators based on a pupil-wave may include the following operations. A pupil-wave is collected when a subject is in a calm state and set as a standard pupil-wave; Obtaining emotional indicators and corresponding emotions used to measure a mental state. The pupil-wave of the subject in each emotional state is collected and set as an emotional pupil-wave; According to the standard pupil-wave, a bandwidth and differential pupil-wave corresponding to each emotion are calculated; The standard, emotional, bandwidth and differential pupil-wave are input into a pre-trained deep convolutional neural network to obtain index values of emotional indicators.
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公开(公告)号：US20170220905A1
公开(公告)日：2017-08-03
申请号：US15309784
申请日：2014-09-05
Applicant: BEIJING UNIVERSITY OF TECHNOLOGY
Inventor： Mi LI , Shengfu LU , Yu ZHOU , Ning ZHONG
CPC classification number: G06K9/6269 , G06K9/0061 , G06K9/42 , G06K9/6232
Abstract: A normalization method in grouped feature data for recognizing human cognitive states, comprising: (1) divide feature data into groups; (2) selecting normalization functions and estimating grouping parameters; (3) building grouped normalization functions, substitute normalization function parameters of each group into its normalization function, the normalization mapping relationship of each group is get; (4) grouped normalization processing, each group uses corresponding normalization function to transfer the feature data to finish feature normalization. The entire feature normalization method can only solve the divers data distribution problem between feature and feature, it can not solve the problem of the large difference of inner data distribution, the grouped normalization methods provided in the invention reserve the advantages of entire feature normalization method, while at the same time, the large inner distribution of feature data is reduced, the accuracy of classification is improved, the grouped normalization method in the invention have strong robustness.
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3.发明公开公开(公告)号：US20240212389A1
公开(公告)日：2024-06-27
申请号：US18528827
申请日：2023-12-05
Applicant: BEIJING UNIVERSITY OF TECHNOLOGY
Inventor： Mi LI , Yanbo CHEN , Jianhui CHEN , Shengfu LV
IPC: G06V40/16
CPC classification number: G06V40/176
Abstract: A joint expression coding system based on static and dynamic expression images is disclosed, including an image preprocessing module, a dynamic expression image generation module, a dynamic weight image generation module, and a joint expression coding image generation module. A joint expression coding method based on the joint expression coding system is also disclosed. A static expression image and a dynamic expression image are combined into one image according to the coding method by adopting the joint expression coding system and method based on the static and dynamic expression images, whereby static expression information and dynamic expression information can be represented at the same time, thus improving the emotion recognition capability based on facial expressions.
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