Designing a component for classifying objects and interpreting their actions using computer vision and machine learning methods
Abstract
Designing a component for classifying objects and interpreting their actions using computer vision and machine learning methods
Incoming article date: 09.04.2025The article presents aspects of designing an artificial intelligence module for analyzing video streams from surveillance cameras in order to classify objects and interpret their actions as part of the task of collecting statistical information and recording information about abnormal activity of surveillance objects. A diagram of the sequence of the user's process with active monitoring using a Telegram bot and a conceptual diagram of the interaction of the information and analytical system of a pedigree dog kennel on the platform "1С:Enterprise" with external services.
Keywords: computer vision, machine learning, neural networks, artificial intelligence, action recognition, object classification, YOLO, LSTM model, behavioral patterns, keyword search, 1C:Enterprise, Telegram bot