Ta'lim innovatsiyasi va integratsiyasi

AN ANALYSIS AND IMPLEMENTATION OF OBJECT RECOGNITION ALGORITHMS FOR SURVEILLANCE SYSTEMS

Hamiyev A.T

Kholiyorov Kh.A

Toshboey J.S

Ключевые слова: Keywords: Object recognition, video surveillance, machine learning, OpenCV, TensorFlow, PyTorch, background modeling, boosting algorithms

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Аннотация

Abstract
This paper delves into the development of algorithms for recognizing abandoned
objects in video surveillance systems. With the increasing importance of security in
public spaces, such as airports and stadiums, the need for efficient and accurate video
analysis tools has become paramount. This study explores various methodologies,
including statistical methods, background modeling, and boosting techniques, to
improve object detection accuracy. Additionally, the implementation of these
algorithms using Python and machine learning frameworks such as OpenCV,
TensorFlow, and PyTorch is discussed.

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Библиографические ссылки

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