ObjectVideo Labs is a pioneer in the fields of video analytics and computer vision, with technology that extracts meaning and intelligence from video streams in real-time to enable object tracking, pattern recognition and activity identification.
ObjectVideo Labs was one of the earliest commercial innovators in the field of Computer Vision. We detect, identify, track, and interpret information from ever-expanding streams of video data, including from hand-held devices, residential and commercial security systems, and vast public IP video deployments.
ObjectVideo Labs’ mobile applications turn smartphones into easy-to-use intelligence gathering devices, providing real-time access to relevant video streams, target metadata and alerts.
ObjectVideo Labs keeps pace with the most recent developments related to geo-location, including the continual generation of geo-registration data from GPS transponders, automatic target hand-off from one asset to another, 3D reconstruction, and query/retrieval.
In this example mobile application, objects and events are identified in a map view and correlated with an augmented view of the mobile device’s camera view.
For airborne vehicles monitoring an area, the geospatial data of objects in that area is frequently imprecise. OVL has developed a variety of approaches to mitigate this imprecision, allowing real-time overlay of GIS data (LIDAR, road networks, compass, etc.).
In the following example, a map-based interface monitors maritime objects and displays tracking, geolocation, and velocity data for selected objects. The user may also place rules and view triggered alerts.
Our analytical framework accommodates ever greater variations in video source placement, simultaneously tracks multiple targets, and effectively manages large volumes of data. We can identify increasingly complex patterns, and display data in intuitive ways to make it easy for users to understand, share and make decisions.
License plate recognition is limited in that it only works under certain constrained environments. ObjectVideo Labs vehicle matching algorithms can augment vehicular identification systems by using other classification and identification criteria, such as vehicle shape and size.
Is the storage room being occupied at odd hours? Is office space being used as efficiently and effectively as possible? Video analytics can shed light on patterns and anomalies to help drive smart business decisions.
Understanding the flow of people or vehicles through critical access points allows for better management of security and staffing resources.