FIELD: data processing.
SUBSTANCE: invention relates to a method of detecting prohibited objects and unauthorized actions in a video stream. Method is carried out by a computer system comprising at least one data processing device, memory storing databases, as well as a graphics accelerator, and comprises steps of: receiving video data from at least one video camera in real time, forming a queue of real-time data in the form of video frames, key frames are extracted from the obtained queue and stored in a data storage; for the obtained key frames, feature maps of objects in the frame are extracted using an artificial neural network and stored in the feature storage, the prepared feature maps are sent to the input of a group of artificial neural networks having different architectures, where each artificial neural network performs detection of its type of action or object, performing feature maps distribution on graphic accelerator cores for parallel detection of prohibited objects and unauthorized actions, wherein each artificial neural network is configured to receive the same set of features at the input, identifying the detected violation in the event that the vector of the probability of the presence of the violation, obtained by the common group of artificial neural networks, exceeds the threshold value, sending a notification on recognized prohibited objects and unauthorized actions to the client device.
EFFECT: high accuracy and speed of recognizing objects and unauthorized actions based on streaming video data by using several artificial neural networks.
1 cl, 2 dwg
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Authors
Dates
2024-08-01—Published
2023-05-03—Filed