BSD 2019 - 1st International Workshop on Big Surveillance Data Analysis and Processing

Organizers
Weiyao Lin (wylin-AT-sjtu.edu.cn), Shanghai Jiao Tong University, China.
John See (johnsee-AT-mmu.edu.my), Multimedia University, Malaysia.
Michael Ying Yang (michael.yang-AT-utwente.nl), University of Twente, the Netherlands.
Website
https://weiyaolin.github.io/ICME2019W.html
Description
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. 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, with the fast increase of semantic data (e.g., objects' trajectory & bounding box) extracted by video analysis techniques, the semantic data have become an essential data type in surveillance systems, introducing new challenging topics, such as efficient semantic data processing and semantic data compression, to the community. Thirdly, with the rapid growth from the static centric-based processing to the dynamic collaborative computing and processing among distributed video processing nodes or cameras, new challenges such as multi-camera joint analysis, human re-identification, or distributed video processing are being issued in front of us. The requirement of these challenges is to extend the existing approaches or explore new feasible techniques.
Scope and 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:
Event detection, action recognition, and activity analysis in surveillance videos
Multi-camera joint analysis and recognition
Object detection and tracking in surveillance videos
Recognition and parsing of crowded scenes
Human re-identification
Summarization and synopsis on surveillance videos
Surveillance scene parsing, segmentation, and analysis
Semantic data processing and compression in surveillance systems
Facial property analysis