Autonomous face tracking camera system dengan implementasi algoritma haar cascades

Budijanto, Joshua (2019) Autonomous face tracking camera system dengan implementasi algoritma haar cascades. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Nowadays there are a lot of video creators who prefer to work alone. To maximize the end result they need a skilled camera operator-like system that is able to track the user. This report discusses the development of such system that is able to track the user’s face and record the session. By design, this autonomous system was built to eliminate the presence of a skilled camera operator. Two items among of hardware used are computer and microcontroller. While at software side, it can be listed Arduino program and Python IDE that linked through serial communication. Haar-cascade classifier and detectMultiScale OpenCV module are used to detect the human face. The built system was tested to detect user’s face in three stages: while the user stood still, moved, and being tracked. The first and second test results show a 100% success rate; while the third test gives 98.56% success. To conclude, the tested system functions properly. Di era modern ini, terdapat banyak content creator yang bekerja seorang diri. Untuk menghasilkan video yang maksimal dibutuhkan sebuah sistem yang menyerupai seorang operator kamera yang mampu bergerak mengikuti pengguna. Dalam penelitian ini, dibentuk sebuah sistem perekaman yang mampu mengikuti wajah pengguna sebagai pengganti seorang operator kamera. Dua perangkat keras utama sistem adalah sebuah komputer dan sebuah kontroler mikro. Dari sisi perangkat lunak, digunakan program Arduino dan Python IDE yang terhubung melalui komunikasi serial. Dalam pendeteksian wajah, digunakan classifier wajah yang dibuat menggunakan algoritma haar cascades dan modul OpenCV dan detectMultiScale. Sistem telah diuji dalam tiga tahap. Ketika pengguna diam, bergerak dan diikuti. Dari hasil pengujian pertama dan kedua diperoleh persentase keberhasilan sebesar 100 persen, sedangkan pada pengujian ketiga diperoleh persentase keberhasilan sebesar 98,56 persen, sehingga dapat disimpulkan bahwa sistem bekerja dengan baik.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Budijanto, JoshuaNIM00000021825joshuabudijanto@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorPutra, Alfa SatyaNIDN0412098503UNSPECIFIED
Thesis advisorAribowo, ArnoldNIDN0304057602UNSPECIFIED
Uncontrolled Keywords: python ; haar-cascade ; haar-cascades ; face detection ; serial communication ; face tracking ; arduino; pendeteksian wajah ; komunikasi serial ; pengikutan wajah ; kamera
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions: University Subject > Historic > Faculty/School > Computer System Engineering
Historic > Faculty/School > Computer System Engineering
Depositing User: Users 2913 not found.
Date Deposited: 19 Nov 2019 07:15
Last Modified: 20 Apr 2020 07:40
URI: http://repository.uph.edu/id/eprint/5706

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