Development of a Face Tracker Using OpenCV and Arduino

Daniel Aliu, Kumater Peter Ter

Abstract


This paper introduces a novel application that harnesses the capabilities of OpenCV's Haar cascade classifiers to achieve precise human face detection. This is complemented by the integration of a pan/tilt servomechanism, under the control of an Arduino UNO, to enable real-time face tracking. The proposed approach employs a multi-stage classification process that efficiently identifies human faces while effectively filtering out background elements. The coordinates of the detected faces, provided by OpenCV, are seamlessly transmitted to the Arduino UNO using pyserial, facilitating the necessary adjustments through servo motors. The collaborative pan/tilt mechanism exhibits dynamic responsiveness, allowing the camera to dynamically adjust by up to 2 degrees, ensuring a consistent alignment with the identified face. This amalgamation of computer vision and embedded systems exemplifies the synergy between the two domains, opening avenues for various applications such as surveillance and human-computer interaction. This convergence promises pioneering advancements in the realm of responsive automation and innovative technological development.


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References


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