The 17 thIEEE Int'l Conf on Advanced Video and Signal-based Surveillance
November 16-19, 2021 | Virtual
1. 4th International Workshop on Small-Drone Surveillance, Detection and Counteraction Techniques
In the last few years the popularity of small Remotely Piloted Aircraft Systems (RPAS) and more generally (also autonomous) “drones”, has exponentially increased due to the availability of low-cost off-the-shelf products, including build-from-scratch and DIY kits. At the same time, issues regarding safety, privacy and security aspects are arising. There is inded a gap in current surveillance systems for the detection of such flying systems, which can be used for illegal activities such as smuggling of drugs or espionage, as well as for carrying explosives or chemical weapons. Their low cost and very small radar signature is making them, unfortunately, a favourite platform for terrorists. Several surveillance and detection technologies are under investigation at the moment, including LIDAR, passive acoustic sensors, passive radio detection and video analytics. However, several challenges must be faced to lower the probability of false alarm, increase the surveillance range and detection rate, as well as to promptly put into action the most appropriate countermeasures according to the operating scenario.
This workshop aims at bringing together researchers from both academia and industry, to share recent advances in the field of small-drone surveillance, detection and counteraction techniques.
2. DeepView: Global Multi-Target Visual Surveillance Based on Real-Time Large-Scale Analysis
In recent years, there has been great progress in demand for visual surveillance systems and intelligent cities capable of providing accurate traffic measurements and essential information for user-friendly monitoring and real-world applications. It is a very practical and essential system that is based on large-scale camera network systems consisting of object detection, tracking, re-identification, and human behavior analysis. However, in many emerging applications, there are still main challenges due to the real-world scenes taken by large-scale cameras, such as illumination changes, dynamic backgrounds, poor data quality, and the lack of high-quality models. In order to tackle key challenges, researchers and engineers strive for developing robust algorithms that can be applied to large-scale surveillance systems. Based on our fundamental knowledge, we want to further upgrade our knowledge of the topic through cooperation with various researchers. In this workshop, we seek original contributions reporting the most recent progress on different computer vision methodologies for surveillance analysis of large-scale visual content and its wide applications that will help make smart systems.