Smart Camera Sensor Networks

Dear Colleagues,

Today more than ever, we are witnessing an uncontrolled proliferation of surveillance cameras in our cities. Many of these cameras have sufficient computing power to process images autonomously and are able to communicate over high-speed networks and in the near future wirelessly over the 5G network. This grid potentially constitutes a network of intelligent cameras with great potential still largely unexplored in its practical applications. For example, video analysis and the extraction of semantic information from the scene can be carried out in a distributed way, implementing advanced strategies of cooperative vision, such as federated learning techniques. In anomaly detection applications, the use of these networks can greatly benefit from the cooperative vision offered by smart cameras.

To tackle the complexity of a distributed approach, cooperative vision and federated learning techniques can leverage the key features of edge and fog computing in mobile 5G networks, which provide broadband and narrowband architectures through high-performance and energy-hungry solutions as well as limited performance and energy-saving ones.

The goal of this Special Issue is to invite high-quality, state-of-the-art research papers that deal with challenging issues in smart camera sensor networks. We solicit original papers of unpublished and completed research that are not currently under review by any other conference/magazine/journal. Topics of interest include but are not limited to the list below.

• Embedded vision programming
• Distributed video coding
• Self-reconfiguring camera networks
• Self-organizing smart cameras
• Wireless and mobile image sensor networks
• Network coding
• Compressive Sensing
• Context-aware networks
• Distributed video analytics
• Distributed video and image retrieval
• Resource management and task allocation
• Data aggregation and information fusion
• Collaborative object recognition and extraction
• Multicamera intelligent video analytics
• Multicamera object detection
• Machine learning in distributed camera networks
• Federated learning
• Edge, fog, and ambient computing for video
• Real-time computer vision

Manuscript Submission Information

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