Scope
With the rapid growth of video surveillance applications and services, the amount of surveillance videos has become extremely “big” which makes human monitoring tedious and difficult. Therefore, there exists a huge demand for smart surveillance techniques that can perform monitoring in an automatic or semi-automatic way. A number of challenges have arisen in the area of big surveillance data analysis and processing. Firstly, with the huge amount of surveillance videos in storage, video analysis tasks such as event detection, action recognition, and video summarization are of increasing importance in applications including events-of-interest retrieval and abnormality detection. Secondly, semantic data (e.g. objects' trajectory and bounding boxes) has become an essential data type in surveillance systems owing much to the growth of its size and complexity, hence introducing new challenging topics, such as efficient semantic data processing and compression, to the community. Thirdly, with the rapid growth from static centric-based processing to dynamic computing among distributed video processing nodes/cameras, new challenges such as multi-camera analysis, person re-identification, or distributed video processing are being issued in front of us. To meet these challenges, there is a great need to extend existing approaches or explore new feasible techniques.

This is the 3rd edition of our workshop. The first two were organized in conjunction with ICME 2019 (Shanghai, China) and ICME 2020 (London, UK)

This workshop is intended to provide a forum for researchers and engineers to present their latest innovations and share their experiences on all aspects of the design and implementation of new surveillance video analysis and processing techniques. Topics of interests include, but are not limited to:  

• Action/activity recognition, and event detection in surveillance videos
• Multi-camera surveillance networks and applications
• Surveillance scene parsing, segmentation, and analysis
• Crowd parsing, estimation and analysis
• Person, group or object or re-identification
• Summarization and synopsis of surveillance videos
• Big Data processing in large-scale surveillance systems
• Distributed, edge and fog computing for surveillance systems
• Low-resolution video analysis and processing: Recognition and object detection, restoration, denoising, enhancement, super-resolution
• Scalable surveillance video analysis with fast model inference and low memory footprint
• Surveillance from multiple modalities, not limited to: UAVs, satellite imagery, dash cams, wearables.

Authors are invited to submit a full paper (2-column standard format according to ICME 2021 guidelines, max. 6 pages total incl. references) electronically via https://cmt3.research.microsoft.com/ICMEW2021/

Important Dates
Paper Submission Due Date: March 13, 2021 [11:59 p.m. PST]
Notification of Acceptance/Rejection: March 27, 2021
Camera-Ready Due Date: April 6, 2021

Organizers
Weiyao Lin, Shanghai Jiao Tong University, China (wylin@sjtu.edu.cn)
John See, Multimedia University, Malaysia (johnsee@ieee.org)
Xiatian Zhu, Samsung AI Centre, Cambridge, UK (eddy.zhuxt@gmail.com)