Computer Vision for Surveillance

Dear Colleagues,

While automatic video surveillance has led to early successful research in tasks such as unattended baggage detection, loitering detection and virtual fences, new tasks are now being explored, such as violence detection, weapon detection, COVID-19-related applications, etc. Despite their complexity, such applications are being fueled by powerful deep learning methodologies. In most cases early detection is crucial to save lives and reduce risks. The purpose of this Special Issue is to provide an academic platform to publish high-quality research papers on the applications of innovative AI algorithms to video surveillance.

The potential topics of interest include but are not limited to the following:

• Violence detection;
• Aggressive behavior detection;
• Fight detection;
• Vandalism detection;
• Firearm detection;
• Knife detection;
• Suspicious object detection;
• Motion detection;
• Object tracking;
• Scene analysis;
• COVID-19 applications (mask detection, thermal imaging, distancing, etc.);
• Combination with other modalities or sensors (i.e., sound, multispectral, 3D, etc.);
• Violence detection from mobile platforms (i.e., drones) or PTZ cameras;
• Real-life applications;
• Datasets.

Dr. Oscar Deniz Suarez
Dr. Juan Antonio Álvarez García
Dr. Noelia Vállez Enano
Guest Editors

Manuscript Submission Information

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