周成菊副研究员

职称：副研究员

yh533388银河

Email:cjzhou@scnu.edu.cn

个人简介

教育背景

（1）2012.04-2019.03, 大阪大学, 计算机科学专业（工学博士）

（2）2011.10-2012.04, 大阪大学研究生学习

（3）2010.10-2011.09, 东北师范大学，基础日语学习

（4）2008.09-2010.12, 大连理工大学(985/211) 信息与信号处理专业（工学硕士）

（5）2004.09-2008.06, 大连理工大学(985/211) 电子信息工程专业（工学学士）

工作经历

2020.05-至今，yh533388银河，yh533388银河，特聘副研究员

2019.04-2020.03, 大阪大学产业科学研究所, 复合智能媒体（八木）实验室 特任研究员

团队主页

http://www.scholat.com/team/hbci

研究领域

计算机视觉、模式识别、深度学习和（人）步态/动作分析。

研究的主要方向有：

(1)基于步态的情绪识别（Gait-Based Emotion Recognition） —包括基于深度学习的步态特征表征，基于深度学习的半监督、迁移学习。

(2)基于步态的身份识别（Gait Recognition）— 包括背包、拍摄角度、服饰变换和遮挡问题。

(3)行为识别和评估（Human Action Recognition and Evaluation) — 包括人体3D骨骼提取，基于深度学习的动作描述。

(4)基于步态的健康评估（Health Assessment by Gait） —包括步态和身体健康及认知健康的关系分析。

欢迎对计算机视觉有兴趣的硕士研究生报考（邮箱：cjzhou@scnu.edu.cn）。

代表性论文

Chengju Zhou, Daqin Feng, Shuyu Chen, Nianming Ban, Jiahui Pan*. “Portable Vision-based Gait Assessment for Post-stroke Rehabilitation Using an Attention-based Lightweight CNN”. Expert Systems With Applications. (SCI, IF=8.5,中科院一区Top，JCR=Q1, DOI：10.1016/j.eswa.2023.122074)

Chengju Zhou, Jiayu Zeng, Lina Qiu, Shuxi Wang, Pingzhi Liu, Jiahui Pan, “An Attention-based Adaptive Spatial-Temporal Graph Convolutional Network for Long-Video Ergonomic Risk Assessment”, Engineering Applications of Artificial Intelligence. (SCI, IF=8, 中科院二区Top, DOI: 10.1016/j.engappai.2023.107780)

Binyuan Huang, Chengju Zhou*（共同第一作者和通讯作者）, Lewei He, Jiahui Pan. “GaitCTCG: cross-view gait recognition via cascaded residual temporal shift and comprehensive multi-granularity learning”. Applied Intelligence. (SCI, IF=5.3, 中科院二区，DOI：10.1007/s10489-023-05241-9)

Shuxi Wang, Jiahui Pan, Binyuan Huang, Pingzhi Liu, Zina Li, Chengju Zhou*（通讯作者）. “ICE-GCN: An interactional channel excitation enhanced graph convolutional network for skeleton-based action recognition”. Machine Vision and Applications, 2023. (SCI, IF=2.983, JCR=Q2)

Huang, Binyuan, Yongdong Luo, Jiahui Xie, Jiahui Pan, Chengju Zhou*（通讯作者）. "Attention‐aware spatio-temporal learning for multi-view gait-based age estimation and gender classification.” IET Computer Vision, 2022. DOI: 10.1049/cvi2.12165. (SCI, IF=1.95, JCR=Q2)

Chengju. Zhou, Ikuhisa Mitsugami, Yasushi Yagi, “Detection of Gait Impairment by Patch-GEI”, IEEJ Transactions on Electrical and Electronic Engineering, Vol.10, No. S1, 2015. (SCI, IF=1)

.Binyuan Huang, Chengju Zhou*（通讯作者）, Chi Xu; Jiahui Pan*. "GaitMSTP: Multi-Granularity Spatio-Temporal Pyramid for Gait Recognition Under Complex Covariation Conditions." IEEE International Joint Conference on Biometrics (IJCB), 2022. DOI: 10.1109/IJCB54206.2022.10007934. (CCF-C 国际会议 Oral发表)

.Shuxi Wang; Chengju Zhou*（通讯作者）; Jiahui Pan; Pingzhi Liu; Daqin Feng; Zina Li. “STACE-GCN: A Spatio-Temporal-Aware Channel Excited Graph Convolutional Network for Skeleton-Based Action Recognition”. IEEE International Conference on Ubiquitous Intelligence and Computing (UIC), 2022. (CCF-C 国际会议)

Chengju Zhou, Daqin Feng, Lewei He, Nianming Ban, Shuxi Wang, Jiahui Pan*. “Automatic Hemiplegia Gait Assessment for Post-Stroke by an Efficient Hybrid Attention-Based GhostNet”, International Joint Conference on Neural Networks (IJCNN), 2023. (CCF-C 国际会议)

Chengju Zhou, I. Mitsugami, F. Okura, K. Aoki, Y. Yagi, “Growth Assessment of School-Age Children from Dual-Task Observation”, ITE Transactions on Media Technology and Applications (MTA), 2018.

Chengju. Zhou, Ikuhisa Mitsugami, Yasushi Yagi, “performance evaluation of GEI for impairment detection”, 16th Meeting on Image Recognition and Understanding (MIRU) 2013.

Chengju. Zhou, Ikuhisa Mitsugami, Yasushi Yagi, “Which Gait Feature Is Effective for Impairment Estimation”, 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV) 2014.

Chengju. Zhou, Ikuhisa Mitsugami, Yasushi Yagi, “Assessing Cognition Level of Elderly Using Dual-task Stepping”, 18th Meeting on Image Recognition and Understanding (MIRU) 2015.

Chengju. Zhou, Ikuhisa Mitsugami, K. Aoki, F. Okura, Yasushi Yagi, “Age Estimation from Dual-Task Behavior for Comprehensive Growth Assessment of Children”, The International Workshop on Frontiers of Computer Vision (IW-FCV) 2018.

Chengju. Zhou, Ikuhisa Mitsugami, Yasushi Yagi, “an attempt to detect impairment by silhouette-based gait feature”, 22th European Society of Movement Analysis for Adults and Children (ESMAC) 2013.

学术活动

受邀演讲

      2015年11月 在吉隆坡举办的第3回 Asian Conference on Pattern Recognition (ACPR) 的International Workshop on Human Behavior Analysis in the Real World 上演讲。

海报发表

（1）2013年7月 在东京举办的第16回Meeting on Image Recognition and Understanding (MIRU) 会议上发表。

（2）2013年9月 在苏格兰格拉斯哥第22回European Society of Movement Analysis for Adults and Children (ESMAC) 会议上发表。

（3）2014年9月 在冲绳举办的第20回Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV) 上做发表。

（4）2015年7月 在大阪举办的第18回Meeting on Image Recognition and Understanding (MIRU) 会议上发表。

（5）2015年11月 在北京举办的第10回 International Workshop on Robust Computer Vision (IWRCV) 上发表。

（6）2015年12月 在大阪举办的19回 SANKEN International Symposium上发表。

（7）2018年2月 在北海道举办的The International Workshop on Frontiers of Computer Vision (IW-FCV) 上发表。

代表性项目

1.日本政府“战略性的创造研究推进事业” CREST项目“基于步态意图行为模式的人物行为的解析和心理环境构建”中“高龄者步态解析”和“孩子成长状况估计”。（2011-2015，项目总经费：3000万人民币, 参与）

2.广东省基础与应用基础研究基金委员会，广东省自然科学基金面上项目，2024A1515012223，融合脑电信号和人脸表情的多模态情感脑机接口及其在意识障碍评估的应用。（2024-01至 今，15万元，在研，参与）

3.广东省教育厅，广东省普通高校重点领域专项，2023ZDZX2021，多模态情感脑机接口技术及其在意识障碍评估的临床应用（2023-10至今，20万元，在研，参与）

Biography

Chengju Zhou, received the B.S. degree in Electronic and Information Engineering, and the M.S. degree in Signal and Information Processing from Dalian University of Technology, China, in 2008 and 2011 respectively. In 2019, she received her Ph.D. degree in Computer Science from Osaka University, Japan. In 2020, she joined the School of Software, South China Normal University, China, as a Specially Appointed Associate Researcher. Her research interests include computer vision, pattern recognition, deep learning, and human gait/action analysis.