Special Issue "Enabled and Human-centric Computational Intelligence Solutions for Visual Understanding and Application"

Submission Deadline: 31 March 2022
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Guest Editors
Prof. Yizhang Jiang, Jiangnan University, China
Prof. Xin Ning, Chinese Academy of Sciences, China
Prof. Weiwei Cai, Northern Arizona University, USA
Dr. Jing Wu, Cardiff University, UK


At present, computer vision (CV) has opened up a new application field. The characteristics of this field are human-centric, that is, human is the main target and service object of the CV system, and it involves the detection, recognition and understanding of static and dynamic features. Specifically, it includes the detection and recognition of various parts of the human body, such as the body, face, and limbs; human actions include gestures, gait, expressions, movements, behaviors, and emotions. human-centric computational intelligence solutions based on CV have the potential to enter a wide range of business, security, education, engineering, entertainment, consumption and daily life.

However, due to a series of complex factors such as illumination, occlusion, forgery attacks, and posture changes in real application scenarios, there are still many challenges and problems in human-centric image understanding that restrict its further application. In recent years, the research progress of deep learning-based CV has shown its potential in practical applications.

Therefore, the purpose of this special issue is to promote practical applications in this field and provide computational intelligence solutions, focusing on the study of computational intelligence methods in human-centric visual understanding and application. This topic will provide new ideas for deep learning-based CV researchers and help solve computational intelligence problems in human-centric visual understanding. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

· Computational Intelligence approaches for human body posture recognition

· Computational Intelligence approaches for behavior recognition

· Computational Intelligence approaches for person re-identification

· CV-enabled and human-centric computational intelligence solutions for industrial applications

· CV-enabled and human-centric computational intelligence solutions for image and video processing

· Human-centric system modeling and design for daily life applications

· Human-centric computational intelligence tools in educational applications