Hand-Raise Detection Pada Kelas Cendekia Menggunakan Kamera RGB Dan Depth

https://doi.org/10.22146/ijeis.34162

Muhammad Fajar Khairul Auni(1*), Muhammad Idham Ananta Timur(2), Ika Candradewi(3)

(1) Prodi Elektronika dan Instrumentasi, DIKE, FMIPA, UGM, Yogyakarta, Indonesia
(2) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(3) Departemen Ilmu Komputer dan Elektronika, FMIPA UGM, Yogyakarta
(*) Corresponding Author

Abstract


The requisite of intelligent classroom’s to perform the quickest speaker lift determination of speakers in the classroom using the concept of ubiquitous computing where the technology exists but does not feel around. The classroom concept requires several capabilities such as knowing the ideal distance from the camera, performing real-time hand-lifted movements from the speaker using the AdaBoost method, and determining the fastest hand lift from the speaker in real-time. The camera's ideal distance to speakers is about 250 cm. the system has a detection accuracy of 97.485497% and accuracy using coordinates joint point of 98%. The system is also capable of determining the fastest time using AdaBoost with 93.5% accuracy and the accuracy of the fastest hands lifting using coordinates joint point of 95%.

Keywords


Ubiquitous Computing; intelligent classroom; Kinect; Gesture Recognition; AdaBoost

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References

[1] E. Oran, “Integrating Mobile and Ubiquitous Computing in a Smart Classroom to Increase Learning Effectiveness,” Int. Conf. Educ. e-Learning Innov., pp. 1–5, 2012 [Online]. Available: http://ieeexplore.ieee.org/document/6360684/ [Accessed: 25-Feb-2018].

[2] J. Park, K. An, D. Kim, and J. Choi, “Multiple human tracking using multiple kinects for an attendance check system of a smart class,” 2013 10th Int. Conf. Ubiquitous Robot. Ambient Intell. URAI 2013, vol. 25, no. 10, p. 130, 2013 [Online]. Available: http://ieeexplore.ieee.org/document/6677494/ [Accessed: 25-Feb-2018].

[3] H. Hartono, L. Liliana, and R. Intan, “Pendeteksian Gerak Menggunakan Sensor Kinect for Windows,” J. Infra, vol. 3, no. 2, p. pp-375, 2015 [Online]. Available: http://publication.petra.ac.id/index.php/teknik-informatika/article/view/3703/0 [Accessed: 25-Feb-2018].

[4] T. Haryadi, U. Dian, N. Semarang, D. Graphic, U. K. Kali, S. View, S. R. Campaign, I. C. View, and T. Haryadi, “IMPLEMENTASI TEKNIK SABETAN MELALUI KINECT ( STUDI KASUS PENGENALAN GERAK WAYANG KULIT TOKOH ....,” no. April, 2017 [Online]. Available: http://publikasi.dinus.ac.id/index.php/technoc/article/view/786 [Accessed: 25-Feb-2018].

[5] S. Dhali, “Vision based gesture recognition with Kinect sensor,” pp. 1–21, 2015 [Online]. Available: https://www.overleaf.com/articles/vision-based-gesture-recognition-with-kinect-sensor/zdyqxbggxfns.pdf [Accessed: 25-Feb-2018].

[6] W. Kurniawan and A. Harjoko, “Pengenalan Bahasa Isyarat dengan Metode Segmentasi Warna Kulit dan Center of Gravity,” vol. 1, no. 2, pp. 67–78, 2011[Online]. Available: https://jurnal.ugm.ac.id/ijeis/article/view/1964/1769 [Accessed: 29-Feb-2018]

[7] M. Fuad, “Estimasi Jarak Menggunakan Sensor Kinect,” J. Ilm. Miktrotek, vol. 1, no. 1, pp. 5–10, 2013 [Online]. Available: http://journal.trunojoyo.ac.id/jim/article/view/151/151 [Accessed: 25-Feb-2018].

[8] M. Fuad, F. Teknik, U. Trunojoyo, R. Telang, and P. O. Box, “Pengenalan Gestur Semaphore Menggunakan Sensor Kinect,” pp. 266–270, 2014 [Online]. Available: https://informatika.uc.ac.id/wp-content/uploads/2017/11/snapti-2015/(266-270)%20Muhammad%20Fuad%20-%20Pengenalan%20Gestur%20Semaphore%20Menggunakan%20Sensor%20Kinect.pdf [Accessed: 25-Feb-2018].

[9] I. Surya, A. Permana, I. Wijayanto, and E. Susatio, “DETEKSI PENYUSUP BERDASARKAN ANALISIS DEPTH FRAME MENGGUNAKAN KAMERA KINECT INTRUDER DETECTION BASED ON DEPTH FRAME ANALYSIS USING KINECT CAMERA Keterangan : I C ( i ) I B ( i ) = intensitas frame pada pixel ( i ) = intensitas background pada pixel ( i ),” vol. 3, no. 3, pp. 4765–4772, 2016 [Online]. Available: https://repository.telkomuniversity.ac.id/pustaka/121449/deteksi-penyusup-berdasarkan-analisis-depth-frame-menggunakan-kamera-kinect.html [Accessed: 25-Feb-2018].

[10] I. Wijayanto and E. Susatio, “IDENTIFIKASI PERGERAKAN DASAR PADA GAME UNTUK PENGEMBANGAN GESTURE RECOGNITION BERBASIS KINECT Identification of Basic Movement on The Game for A Gesture Recognition Based on Kinect,” vol. 4, no. 2, pp. 1988–1995, 2017 [Online]. Available: http://repository.telkomuniversity.ac.id/pustaka/135849/identifikasi-pergerakan-dasar-pada-game-untuk-pengembangan-gesture-recognition-berbasis-kinect.html [Accessed: 25-Feb-2018].

[11] R. E. Schapire, “Explaining adaboost,” Empir. Inference Festschrift Honor Vladimir N. Vapnik, pp. 37–52, 2013 [Online]. Available: http://rob.schapire.net/papers/explaining-adaboost.pdf [Accessed: 25-Feb-2017].

[12] A. A. Hassan and S. N. Basah, “GESTURE-BASED REMOTE-CONTROL SYSTEM USING COORDINATE FEATURES Abdirizak Abdullahi Hassan and Shafriza Nisha Basah,” vol. 11, no. 8, pp. 4979–4986, 2016 [online]. Available: https://pdfs.semanticscholar.org/0ed5/7772ea3472cb2501c9b65421ee3370ccb137.pdf [Accessed: 25-Feb-2017].



DOI: https://doi.org/10.22146/ijeis.34162

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