Expression recognition algorithm based on CM-PFLD key point detection

Chao Zhang; Siquan Hu; Zhiguo Shi

doi:10.1117/12.2631131

18 March 2022 Expression recognition algorithm based on CM-PFLD key point detection

Chao Zhang, Siquan Hu, Zhiguo Shi

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121682V (2022) https://doi.org/10.1117/12.2631131
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

Facial expression recognition is a hot research topic in artificial intelligence industry and has a good research prospect in various fields. At present, facial expression recognition processes the whole face directly, but the pixel value of non-feature region may bring some interference for feature descriptor extraction. Considering that the cartoon effect of the face can directly reflect the facial expression features. In order to make the network pay more attention to the information of the facial features and their surrounding pixels, this paper proposes an expression recognition algorithm based on key point detection of Covering multi-scale Practical Landmark Detector (CM-PFLD). Under this algorithm, this paper constructs a cartoon expression data set, which only retains the key points of facial expression information, and then classifies facial expression by directly locating the key points of facial expression information. In order to verify the feasibility of the expression recognition method in this paper. The experiment uses Fer2013 and CK data sets to produce cartoon expression data sets, and trains and compares cartoon data sets and original data sets respectively under the same network. The experimental results show that the method proposed in this paper has high detection accuracy and fast speed on standardized and neat data sets. On the data set with more unfavorable factors, the training accuracy of the two methods is similar, but the processing speed of the proposed method is faster. Experimental results show that the proposed method is feasible and effective.

Citation Download Citation

Chao Zhang, Siquan Hu, and Zhiguo Shi "Expression recognition algorithm based on CM-PFLD key point detection", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121682V (18 March 2022); https://doi.org/10.1117/12.2631131

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
14 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Facial recognition systems

Detection and tracking algorithms

Data modeling

Convolution

Drug discovery

Head

Feature extraction

Show All Keywords

Keywords/Phrases

Search In:

Publication Years