Abstract
The article investigates the integration of sensor devices with computer vision algorithms to improve motion tracking systems. The article shows the feasibility of using different types of computer vision algorithms, each of which plays a special role in improving the performance of motion tracking systems. This makes it possible to create motion tracking systems that provide high accuracy, speed, and reliability. Moreover, such systems can work in different lighting conditions and with different types of objects. Computer vision algorithms can detect motion in video images regardless of lighting conditions, and motion sensors can help detect and track objects even in limited visual conditions. A comparative analysis of sensor devices and computer vision algorithms, their type of operation and feasibility of application was performed. We also developed our own face tracking algorithm written in the Python programming language.
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