New Gartner Analyst Report on AI for Computer Vision Highlights Importance of Real-Time Behavior Recognition for Cutting-Edge Video Analytics
viisights, the developer of an innovative behavioral understanding systems for real-time video intelligence, announced that the company has been named as a Cool Vendor by the leading analyst firm Gartner.
Gartner has designated viisights as a Cool Vendor in its Cool Vendors in AI for Computer Vision: Balance Business Risk and Reward published by Nick Ingelbrecht, Nikki Zaveri-Kapacee, Tuong Nguyen, Anshul Gupta and CK Lu in August 2018.
In this analyst report, Gartner highlights the importance of “real-time behavior recognition” and states that “automated scene analysis used to generate real-time insight into human/object behavior is at the cutting edge of video analytics today.”
“We are proud to be named a Gartner Cool Vendor and, yes, we certainly agree that real-time behavior understanding is an essential for generating important new value from video analytics going forward,” stated Asaf Birenzvieg, co-founder and CEO of viisights. “We believe that this Cool Vendor recognition is important validation of the growing demand we are experiencing for our behavioral understanding systems and their unique AI-driven capability of understanding the behavioral context of scenes in live video streams.”
viisights’ video analytics technology delivers high-performance, artificial intelligence capabilities that extract new actionable insights by providing a real-time behavioral understanding of the context of scenes, events and actions within massive amounts of live video streams. By providing a contextual understanding of real-time video streams, viisights and its technology enriches the existing legacy video analytic systems, which focus only on object identification and classification.
The viisights technology is based on real-time temporal and holistic video streaming analysis. viisights uses video clips rather than discrete images for training its core AI engine, which are based on convolutional neural networks and LSTM models. These unique structures are used to create a unique event signature that includes the scene participants and their extracted features, such as positioning, movement, size and relationship with other objects. During runtime streaming, these signatures are being searched for and compared.
Based on this video understanding technology, viisights is capable of understanding the context of actions and events in live video streams and clearly distinguish between a person walking, running or falling in the street or someone behaving suspiciously or violently in a crowded public space.
viisights’ technology has applications for the safe and smart cities, smart businesses, critical infrastructures, transportation hubs, autonomous and shared mobility. The company bringing its technology and applications to market through a growing network of relationships with system integrators and similar sales channel partnerships as well as through its direct sales force.
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