SISTEM PELACAKAN VIDEO OTOMATIS, BERBASIS DETEKSI WAJAH PADA PERANGKAT ANDROID
When taking photos or videos on a smartphone often obtained unsatisfactory results, due to lack of focus on the moving objects such as human faces. Needed someone else to drive the smartphone manually, so the photos or videos taken, can capture a moving object maximally. In this research designed a...
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| Main Authors: | , |
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| 格式: | Theses and Dissertations NonPeerReviewed |
| 出版: |
[Yogyakarta] : Universitas Gadjah Mada
2014
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| 主題: | |
| 在線閱讀: | https://repository.ugm.ac.id/132033/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=72549 |
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| 總結: | When taking photos or videos on a smartphone often obtained unsatisfactory results, due to lack of focus on the moving objects such as human faces. Needed someone else to drive the smartphone manually, so the photos or videos taken, can capture a moving object maximally. In this research designed a tool that can automatically drive the smartphone, with tracking on a moving person's face, when smartphones taking a video. Digital image processing, implemented on Android devices using the OpenCV library, with cascade classifer and template matching method. From the image captured by the camera, face detection performed and determined the coordinates of the face. Furthermore, the Arduino control the servo which has been prepared in order to drive the Android for tracking and record video right in the face image captured by the camera.
The results of this research is a tool that automatically tracking on the face, using Android smartphones. System testing the influence of light intensity, time of process, testing facial variations, testing the direction of the face towards the camera, facial position shift testing, testing different methods, and testing of constant proportional variation in the system. The result is that the face detection process can be performed on a wide variety of faces. The best face detection process is when a straight face to the position of the camera. Besides, the face detection process best done in a room with light intensity above 1.59 cd (20 lux). Tool is also able to perform precise tracking of the position of the detected face, although the detected face is changing locations. There is a lapse of time when Android do face detection on the face of the changing locations of 213.9 milliseconds. |
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