As the leader in the application of intelligent analytics to video surveillance, VideoIQ has extensive experience with machine learning and data analytics algorithms, video storage and object classification, making VideoIQ’s prevention solution highly precise and effective.
With over 25 US and International patents, VideoIQ continues to grow their portfolio with the rapid development of analytics technology.
“This level of commitment and accomplishment blends technology, science and mathematics to a level I am most proud of. Our team continues to push the boundaries in intelligent analytics, allowing cameras to essentially see and think like you do”, said Dr. Mahesh Saptharishi. “We continue to seek and develop new learning algorithms to make active prevention a reality for any market and any camera.”
The 10 latest awarded patents cover the following:
- VideoIQ’s innovative content aware storage technology combines sensing, analysis and mass storage at the edge. Content aware storage enables the industry’s only intelligent all-in-one surveillance solution. The patented storage technology also covers the combination of solid state and traditional mass storage devices, increasing the lifetime of a typical hard disk drive by 5-10X
- VideoIQ continues its innovation in self-learning pattern based video analytics with powerful object pattern tracking and search and fully trainable object classification technology. Pattern based tracking and classification make VideoIQ’s analytics highly accurately with no manual calibration required. Additionally, the patented classifiers are capable of learning both by watching the environment and via feedback from a user: VideoIQ’s innovative Teach-By-Example system
- VideoIQ’s state-of-the-art algorithms run on standard off-the-shelf, low-power processors thanks to a unique and flexible approach that automatically translates any floating point algorithm to a fixed point implementation
US Patents: 8,224,029, 8,280,939 and 8,427,552
UK Patents: GB 2470520, GB 2470677, GB 2492246, GB 2492247, GB 2492248, GB 2491987 and GB 2495030