Uncertainty Learning for Video Systems in Open Environment

Dear Colleagues,

Video processing has always been a frontier topic and an influential research direction in the field of machine computer vision. Most of the research in this field focuses on the use of intelligent technology to analyze the content of video sequences without human intervention, to detect, identify and track suspicious targets in video scenes, and to analyze the behavior of targets and understand the meaning of image content. At present, the method of "deep learning+big data" has achieved excellent recognition performance in many video tasks, and even exceeded the human intelligence level in some tasks. Essentially, knowledge for these video tasks is well estimated and modelled when sufficient data and effective tools are combined. However, in an open environment, due to the uncontrollable quality and content of surveillance data, dynamic changes in categories and data distribution, small amounts of labeled data, noise interference and other reasons, the existing methods show obvious shortcomings in generalization, robustness, interpretability, self-adaptability and other aspects. Therefore, open environment intelligent video processing faces a series of new research problems and needs to explore new theories, models and algorithms.

Therefore, this Special Issue is intended for the presentation of new ideas, advanced theories, and experimental results in the field of video processing, knowledge modeling and uncertainty learning. Topics of interest for this Special Issue include, but are not limited to, the following:

• Video processing technologies, like detection, tracking, segmentation, etc.;
• Video content understanding;
• Natural scene understanding;
• Knowledge discovery and data mining;
• Knowledge graph;
• Multimodal fusion;
• Image processing, recognition and classification;
• Model interpretability;
• Uncertainty learning, open environment incremental learning and continual learning;
• Multi-granularity feature learning;
• Retroactive reasoning.

Prof. Dr. Youxi Wu
Dr. Linhao Li
Prof. Dr. Liang Yang
Dr. Changqing Zhang
Guest Editors

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