A team of researchers at JD AI Research and Beijing University have recently developed a progressive vehicle search system for video surveillance networks, called PVSS. Their system, presented in a paper pre-published on arXiv, can effectively search for a specific vehicle that appeared in surveillance footage. Vehicle search systems could have many useful applications, including enabling smarter transportation and automated surveillance. Such systems could, for instance, allow users to input a query vehicle, search area and time interval to find out where the vehicle was located at different times during the day. Existing vehicle search methods typically assume that all vehicle images are cropped well from surveillance videos, using visual attributes or license plate numbers to identify the target vehicle within these images.
CNL Software has entered into a technology partnership with Herta Security under the CNL Software Technology Alliance Program. Herta develops user-friendly software solutions that enable the integration of facial recognition in security applications. According to the announcement, Herta's deep learning algorithms encode faces directly into small templates, which are very fast to compare and yield more accurate results. This provides a technological advantage when working with partners, as it allows the development of more robust, safer and efficient solutions. IPSecurityCenter PSIM takes a vendor agnostic approach to implement flexible and scalable security management software.
International Data Corporation (IDC) recently published an IDC Innovators report profiling five companies that offer compelling and differentiated computer vision software. The five companies are Algolux, Deep Vision AI, Sighthound, ViSenze, and Umbo CV. Computer vision is an AI technology that allows computers to understand and label images. Use cases include video surveillance, driverless car testing, daily medical diagnostics, and monitoring the health of crops and livestock. AI is used for pattern recognition and learning techniques driven largely by machine learning (ML) and deep learning (DL) algorithms that bring visual understanding capabilities in a growing variety of hardware and software applications.
Artificial intelligence (AI) is improving everyday solutions, driving efficiency in ways we never imagined possible. From self-driving cars to intelligent analytics, the far-reaching impacts of Deep Learning-based technology empower human operators to achieve results more effectively while investing fewer resources and less time. By introducing AI, solutions are not merely powered by data, but they also generate valuable intelligence. Systems which were once leveraged for a narrow, dedicated purpose, can suddenly be engaged broadly across an organization, because the previously under-utilized data can be harnessed for enhancing productivity and performance. When it comes to physical security, for instance, video surveillance is a standard solution.
This new offering is available to service providers such as security integrators, telecoms and alarm and monitoring companies for reselling to their customers. IvedaAI includes a powerful self-contained server with artificial intelligence (AI) software, capable of searching a combination of objects from dozens to thousands of cameras in less than one second. Video analytics have been around for many years, but adoption has been slow because of inaccuracies and high cost. IvedaAI employs 30 patents in AI, big data analytics and cloud computing. It applies a deep learning algorithm (trained, not programmed), automates processes and uses natural language.