Interactive Eyes Face Tracking and Memory Assistance Using Computer Vision

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dc.contributor.advisorAlmusawi, Husam Abdulkareem
dc.contributor.authorAbdelhakim Abdelrazek Mohamed Hamza, Mirna
dc.contributor.departmentDE--Műszaki Kar
dc.date.accessioned2025-09-04T15:37:04Z
dc.date.available2025-09-04T15:37:04Z
dc.date.created2025-05-12
dc.description.abstractThis thesis delves into the development of an interactive robotic eye system that integrates both real-time face recognition and voice-based interaction. It is built using a Raspberry Pi, PCA9685 servo driver, and 3D-printed eye structure, the system aims to deliver dynamic, human-like eye movements with detected faces using the OpenCV, MediaPipe and CVZone libraries. Additionally, a voice assistant powered by speech-to-text and text-to-speech libraries to communicate with users and assist them with features like task reminders, alarms, and object location memory. These tools are used to create a reliable face tracker that includes a responsive assistant side of the project. By merging vision and speech-based interaction, the system offers a step towards social communication and a better human-machine interface. The results demonstrate reliable face tracking and responsive voice assistant functions which demonstrate the potential for utilizing it as a personal companion.
dc.description.courseMechatronical Engineeringen
dc.description.degreeBSc/BA
dc.format.extent64
dc.identifier.urihttps://hdl.handle.net/2437/397254
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectOpenCV
dc.subjectVoice Assistant
dc.subjectFace Tracking
dc.subject.dspaceEngineering Sciences
dc.titleInteractive Eyes Face Tracking and Memory Assistance Using Computer Vision
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