Over recent years, the availability of much larger amounts of data, cheap parallel hardware such as GPU and new machine learning methods such as deep learning have made a significant impact on how data is interpreted. In the UK and worldwide, there is an increased interest to effectively analyse massive unbiased data, generated from very different sources and with many different features such as social networks, surveillance systems, smart cities, cyberphysical systems, address and find solutions on the vulnerability of public spaces and individuals. However, there are serious limitations to the use of conventional monitoring systems where human operators are asked to survey a large number of cameras with a wide geographical coverage or go through enormous amounts of recorded material for forensic investigations. We are keen to see how developments on complex systems, adaptive behaviours, and machine learning methods have impacted the field of crime detection and prevention in particular and the monitoring of public places in general.

This conference follows the successful IDSS (Intelligent Distributed Surveillance Systems) events held in 2003 and 2004 and ICDP 2005, 2006, 2009, 2011, 2013, 2015, 2016 and 2017 to bring together researchers, industry, end-users, law-enforcement agencies and citizens groups to share experiences and explore areas where additional research and development are needed, identify possible collaboration and consider the societal impact of such technologies. Full papers are invited on all aspects of Imaging Surveillance technologies, from academia, industry, NGOs and others, to be selected for oral presentations or posters through a peer-review system. Co-sponsored by the IET's Vision and Imaging Network and the IEEE (UKRI chapters on Circuits and Systems and Instrumentation and Measurements). Accepted and presented papers will be published by the IET and indexed in Inspec (and normally in IEEE Xplore and Scopus).

An indicative, not exclusive, list of relevant topics is:

Surveillance Systems and solutions (system architecture aspects, operational procedures, usability, scalability)
Multi-camera systems
Information fusion (e.g. from visible and infrared cameras, microphone arrays etc)
Learning systems, Cognitive Systems Engineering and video mining
Robust computer vision algorithms (24/7 operation under variable conditions, object tracking, multi-camera algorithms, behaviour analysis and learning, scene segmentation)
Human Machine Interfaces, Human Systems Engineering and Human Factors
Wireless communications and networks for video surveillance, video coding, compression, authentication, watermarking, location-dependent services
Metadata generation, video database indexing, searching and browsing
Embedded systems, surveillance middleware
Gesture and posture analysis and recognition
Biometrics (including face recognition)
Forensics and crime scene reconstruction
X-Ray and terahertz scanning
Case studies, practical systems and testbeds
Data protection, civil liberties and social exclusion issues
Algorithmic bias and transparency for machine learning
AI ethics
Custom FPGA based approximate computing