Analysis of Markerless-Based Tracking Methods of Face Tracker Techniques in Detecting Human Face Movements in 2D And 3D Filter Making

  • M.Ilham Arief Faculty of Computer Science, Universitas AMIKOM Yogyakarta, Yogyakarta
  • Kusrini Kusrini Faculty of Computer Science, Universitas AMIKOM Yogyakarta, Yogyakarta
  • Tonny Hidayat Faculty of Computer Science, Universitas AMIKOM Yogyakarta, Yogyakarta
Abstract views: 227 , PDF downloads: 180
Keywords: Augmented Reality, Markerless-Based Tracking Method, Face Tracking, Light Intensity, Face Angle Position, Face Distance, User Experience Questioner (UEQ) Method

Abstract

The marker-based tracking method is a method that utilizes markers, while the markerless-based tracking method is a method that does not use markers in making AR. In the markerless-based tracking method, there is a face tracker technique. In previous research, no one has discussed the comparison of effectiveness concerning the success and accuracy of using the face tracker technique. Therefore, this study aims to test the effectiveness of the accuracy and accuracy of success with applying the markerless-based tracking method, the face tracker technique, in detecting facial movements. in 2D and 3D AR with light intensity test parameters of 20 Lux, 40 Lux, and 60 Lux with WRGB light color, Face angle position of 30o and 60o, and face distance from camera 50 cm, 100cm, and 150cm. The results of comparison of superior success accuracy are at a distance of 50 cm; with an accuracy rate for 2D AR of 93.22% and 96.63% for 3D. It was concluded that the face tracker technique's markerless-based tracking method works optimally in 3D compared to 2D. This research finds an attractiveness score of 1.865, a perception score of 1.683, an efficiency score of 1.550, a dependability score of 1.638, a stimulation score of 1.500, and a novelty score of 1.013. Quality with an attractiveness value of 1.68, pragmatic quality of 1.56, and hedonic quality of 1.26. This study concludes that 2D and 3D AR face detection positively evaluates user experience and quality.

 

 

Author Biographies

M.Ilham Arief, Faculty of Computer Science, Universitas AMIKOM Yogyakarta, Yogyakarta

 

 

Kusrini Kusrini, Faculty of Computer Science, Universitas AMIKOM Yogyakarta, Yogyakarta

 

 

Tonny Hidayat, Faculty of Computer Science, Universitas AMIKOM Yogyakarta, Yogyakarta

 

 

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Published
2023-01-26
How to Cite
Arief, M., Kusrini, K., & Hidayat, T. (2023). Analysis of Markerless-Based Tracking Methods of Face Tracker Techniques in Detecting Human Face Movements in 2D And 3D Filter Making. Inform : Jurnal Ilmiah Bidang Teknologi Informasi Dan Komunikasi, 8(1), 47-56. https://doi.org/10.25139/inform.v8i1.5684
Section
Articles