FIELD: computer technology.
SUBSTANCE: invention relates to the field of computer technology. A computer vision system in retail contains a set of video cameras for capturing images connected by a single network with a server. The block for capturing the stream from cameras is located on the server and is configured to independently read frames from the stream of a set of video cameras using a queuing mechanism that buffers the frames necessary for processing, and the block captures each current frame from the stream, arriving at a frequency pre-set on the camera, and if the difference between the two fixed time characteristics exceeds or equals the threshold value, the frame is decoded and buffered into the queue variable, and if the queue variable is overflowing, the frame is skipped. The detector block is an artificial neural network that receives frames from the queue formed by the camera stream capture block and returns the coordinates of the contours of predetermined objects to be detected. Analyzer block configured to compare the detected objects detected by the detector unit with the reference states stored in the database and classify the types of inconsistencies. The block for sending notifications and visualization is configured to send the results of the identified inconsistencies of the analyzer block to the graphical user interface.
EFFECT: technical result is to improve the accuracy of detection of small and closely spaced objects.
3 cl, 8 dwg
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Authors
Dates
2022-12-06—Published
2022-11-11—Filed