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Nurdin, Riani
Institut Teknologi Dirgantara Adisutjipto
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mechanical Engineering Public Health Social Sciences Transportation Other

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Hand Gesture-Based Human-Computer Interaction using MediaPipe and OpenCV Putri, Risma Dwi Tjutarjo; Lasmadi, Lasmadi; Kusumaningrum, Anggraini; Nurdin, Riani; Astuti, Yenni
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 2 (2025): August
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i2.3132

Abstract

This study presents the design and implementation of a real-time hand gesture recognition system for directional movement using MediaPipe and OpenCV. The system aims to enhance Human-Computer Interaction (HCI) by recognizing four primary hand gestures—forward, backward, left, and right—based on real-time video input from a standard webcam. The proposed method extracts 21 hand landmarks using MediaPipe, then analyzes landmark displacement to determine the direction of movement. Experiments were conducted under three lighting conditions (bright, moderate, dim) and at three distances (200 cm, 300 cm, and 450 cm). Results show that the system achieved 100% recognition accuracy for all gestures at 200 cm. At 300 cm, accuracy slightly decreased, particularly for backward gestures (down to 77.5%). At 450 cm, performance dropped significantly, with accuracy for some gestures falling below 30%, especially under dim lighting. These findings demonstrate that the proposed system performs reliably at short to medium distances and is sensitive to lighting conditions and user proximity. This research contributes to the development of touchless interfaces for smart environments, presentations, and other interactive applications.
Co-Authors Angelia, Yulia Anggraini Kusumaningrum, Anggraini Arrasyid, Calvin Ali Bangga Dirgantara Adiputra Budiwidodo, Sidik Dhaka, Nikolaus Meo Dindi Asparilla Putri Sutanto Eko Poerwanto Eko Poerwanto Esa Rengganis Esa Rengganis Sulliyartha Esa Rengganis Sullyartha Esa Rengganis, Esa Fajri, Arif Gunawan Gunawan Gunawan Gunawan Gunawan Hanan, Zatil Hanan, Zatil Harliyus Agustian Haruno Sajati Indrayani, Susi Fatma Indrayani, Susi Fatma Khoirullah, Muhammad Habib Nur Kusumaningrum, Maria Deny Lasmadi, Lasmadi Maria Asumpta deny Kusumaningrum Maria Asumpta Deny Kusumaningrum, Maria Asumpta Deny Marni Astuti Marni Astuti Marni Astuti Marni Astuti, Marni Nurfi Ahmadi Nurfi Ahmadi, Nurfi Prasidananto Nur Santoso Prasidananto Nur Santoso Prattiwi, Elisabeth Anna Priyo Yudo Abadi Putri, Risma Dwi Tjutarjo Rahmawati, Fajar Khanif Ramadhan Rafiq Ibrahim Roychan Yoga Pratama Rully Medianto Sabil Pradana, Adi Yudha Santoso, Prasidananto Nur Satrio, Rayhan Fajar Suhanto Suhanto Suhanto Suhanto, Suhanto Sullyartha, Esa Rengganis Utomo, Bagus Wahyu Uyuunul Mauidzoh yasrin zabidi Yasrin Zabidi, Yasrin Yenni Astuti, Yenni Yulia Ratna Sari, Yulia