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Donny Rhomanzah
Telkom University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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LBP Advantages over CNN Face Detection Method on Facial Recognition System in NOVA Robot Luqman Bramantyo Rahmadi; Kemas Muslim Lhaksmana; Donny Rhomanzah
Indonesia Journal on Computing (Indo-JC) Vol. 5 No. 2 (2020): September, 2020
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2020.5.2.456

Abstract

Network-optimized virtual assistant (NOVA) is a robot developed by Bandung Techno Park (BTP) that can interact with humans for various purposes, such as a receptionist robot. NOVA robot is still in development and one of the main focuses is adding face recognition features so that the robot can actively greet and interact with humans. Therefore, we propose a face recognition and tracking system based on neural networks. This system is developed using the Google FaceNet feature extraction method. Previously, face detection in NOVA robot was implemented by employing the multi-task cascaded convolutional networks (MTCNN) method, whereas face tracking on the system was realized by using the modification of the MOSSE object tracking method. However, we found that the implementation of MTCNN in NOVA robot cannot run better than 30 fps. Therefore, this paper aims to solve this issue by investigating conventional face detection methods that could outperform MTCNN in this regard. Tests conducted on the ChokePoint dataset demonstrates that the system with LBP can achieve 30.44 fps framerate with a precision of 95% and recall of 83%. The test results show that LBP is not only better than MTCNN in identifying faces but also more efficient to compute.
Sistem Kecerdasan Buatana Untuk Robot Asisten Berbasis Algoritma Case Based Reasoning Donny Rhomanzah; Angga Rusdinar; Unang Sunarya
eProceedings of Engineering Vol 2, No 1 (2015): April, 2015
Publisher : eProceedings of Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Dewasa ini kebutuhan teknologi khususnya robot dalam hal alat penunang aktivitas manusia semakin meningkat. Kebutuhan akan daya dukungan robot terhadap asistensi pekerjaan sudah bukan suatu hal yang aneh lagi. Namun tetap saja masih terdapat sebuah dinding pemisah anatara manusia dan robot, salah satunya adalah dalam segi sistem komunikasi antara manusia dan robot yang dirasa masih sulit. Untuk mengatasi hal tersebut perlu dibuat suatu sistem asistensi cerdas yang disertai oleh antarmuka yang relatif lebih mudah. Metode yang dapat digunakan untuk mengatasi hal tersebut adalah dengan algoritma case based reasoning yang dipadukan dengan pengolahan suara meliputi Speech Recognition dan Speech Synthesis. Perpaduan metode ini diharapkan dapat mensistesis kemampuan berkomunikasi verbal pada manusia kedalam bentuk sistem cerdas. Hasil dari penelitian ini adalah sebuah robot asisten yang dapat berinteraksi melalui komunikasi lisan dengan penggunanya melalui percakapan dalam bahasa Inggris. Adapun ruang lingkup fungsi yang dikuasai oleh robot mampu memahami perkataan pengguna dengan akurasi rata-rata 70% pada ruangan sunyi dan 60% pada ruangan ramai.Kata Kunci : Case Base Reasoning (CBR), Robot Asisten, Speech Recognition, Speec Synthesis.
Co-Authors Angga Rusdinar Kemas Muslim Lhaksmana Luqman Bramantyo Rahmadi Unang Sunarya