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)