Introduction

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 which 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 the static centric-based processing to the 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 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)


Scope & Topics

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 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.

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Call for Papers

Important Dates
    Paper Submission Due Date: March 13, 2021 March 20, 2021
    Notification of Acceptance/Rejection: March 27, 2021 April 6, 2021
    Camera-Ready Due Date: April 13, 2021
    Workshop Date and Venue: TBD
Format Requirements & Templates
    Length: Papers must be no longer than 6 pages, including all text, figures, and references.
    Format: Workshop papers have the same format as regular papers. See the templates below. Submitted paper does not need to be double blind.
    Important: A complete paper should be submitted using the above templates.
Submission Details
    Paper Submission Site: https://cmt3.research.microsoft.com/ICMEW2021
    (Please make sure your paper is submitted to the correct track)
    Submissions may be accompanied by up to 20 MB of supplemental material following the same guidelines as regular and special session papers.
    Review: Reviews will be handled directly by the Organizers and the Technical Program Committee (TPC).
    Presentation guarantee: As with accepted Regular and Special Session papers, accepted Workshop papers must be registered by the author deadline and presented at the conference; otherwise they will not be included in IEEE Xplore. A workshop paper is covered by a full-conference registration only.
    Conference Location: Shenzhen, China

Schedule

To be announced...


Speakers

To be announced...


Organizers

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Weiyao Lin
 wylin AT sjtu.edu.cn
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John See
 johnsee AT ieee.org
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Xiatian Zhu (Eddy)
 eddy.zhuxt AT gmail.com

Contact

Please feel free to send any question or comments to:
johnsee AT ieee.org, wylin AT sjtu.edu.cn, eddy.zhuxt AT gmail.com