Association of socioeconomic status and health-related behavior with elderly health in China.

Autor: Fubaihui Wang, Qingkai Zhen, Kaigang Li, Xu Wen

Publikováno v: PLoS ONE, Vol 13, Iss 9, p e0204237 (2018)

Previous health studies have focused on the correlation between socioeconomic status (SES) and health. We pooled data from the Chinese Longitudinal Healthy Longevity Survey (N = 9765) conducted in 2011, and examined the association of SES and health-

Externí odkaz: https://doaj.org/article/4bc336e00ed44a2a998cbd261af2fcdc

Study on a Footwork Training and Testing System

Autor: Qi Hu, Qi Chen, Yongqing Liu, Qingkai Zhen

Publikováno v: Proceedings, Vol 2, Iss 6, p 537 (2018)

In the sport science fields, for a long time there are various attempts to explore more advanced technology in order to collect kinds of information concerned during athletes training and matches. In the paper, a footwork training and testing system

Externí odkaz: https://doaj.org/article/07e0ba51db2d45a59a9f4cf089077292

Magnifying Subtle Facial Motions for Effective 4D Expression Recognition

Autor: Hassen Drira, Mohamed Daoudi, Qingkai Zhen, Di Huang, Yunhong Wang, Boulbaba Ben Amor

Publikováno v: IEEE Transactions on Affective Computing
IEEE Transactions on Affective Computing, Institute of Electrical and Electronics Engineers, 2019, 10 (4), pp.524-536
IEEE Transactions on Affective Computing, 2019, 10 (4), pp.524-536

In this paper, an effective pipeline to automatic 4D Facial Expression Recognition (4D FER) is proposed. It combines two growing but disparate ideas in Computer Vision -- computing the spatial facial deformations using tools from Riemannian geometry

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::75f543d7b766f73f9fb3fc747421ffc8

Magnifying subtle facial motions for 4D Expression Recognition

Autor: Boulbaba Ben Amor, Hassen Drira, Di Huang, Yunhong Wang, Mohamed Daoudi, Qingkai Zhen

Publikováno v: 23rd International Conference on Pattern Recognition, ICPR 2016
23rd International Conference on Pattern Recognition, ICPR 2016, Dec 2016, Cancún, Mexico. pp.2252-2257, ⟨10.1109/ICPR.2016.7899971⟩
ICPR

International audience; In this paper, we propose an effective approach for automatic 4D Facial Expression Recognition (FER). The flow of 3D facial scans is first modeled to capture spatial deformations based on the recently-developed Riemannian appr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2c98500e18ab513ce0f49c63b1e75e32
https://hal.archives-ouvertes.fr/hal-01521628/document

Learning Encoded Facial Curvature Information for 3D Facial Emotion Recognition

Autor: Meng Meng, Qingkai Zhen, Yiding Wang

Publikováno v: ICIG

In current 3D facial expression recognition system, feature extraction has always been a critical point. We focus on encoding feature by using curvature information. 3D facial expression images are described by means of four images which gray level a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6575b4406b7c6d4a9cd98e5d2332b63f
https://doi.org/10.1109/icig.2013.112