Efficient Gesture based Language Recognition using SVM and Lloyd’s Algorithm
Abdul Khader1, Muhammad Thouseef2, Akbar Ali3, Ahamad Irfan4
1Abdul Khader, Assistant Professor, Department of Computer Science & Engineering, Bearys Institute of Technology Innoli, Mangaluru (Karnataka), India.
2Muhammad Thouseef, Department of Computer Science & Engineering, Bearys Institute of Technology Innoli, Mangaluru (Karnataka), India.
3Akbar Ali, Department of Computer Science & Engineering, Bearys Institute of Technology Innoli, Mangaluru (Karnataka), India.
4Ahamad Irfan, Department of Computer Science & Engineering, Bearys Institute of Technology Innoli, Mangaluru (Karnataka), India.
Manuscript received on 21 July 2019 | Revised Manuscript received on 03 August 2019 | Manuscript Published on 10 August 2019 | PP: 927-930 | Volume-8 Issue-2S3 July 2019 | Retrieval Number: B11750782S319/2019©BEIESP | DOI: 10.35940/ijrte.B1175.0782S319
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Undertaking in the field of human-computer interaction (HCI) and computer vision. 10 years prior to the undertaking appeared to be practically unsolvable with the data given by a single RGB camera. In this work, we have actualized a presumable exact strategy to perceive static gestures or image frames from a live camera or video data. As Hand Gesture Recognition is identified with two noteworthy fields of image processing and AI (machine learning), in this way, this report likewise refers to the different tools and APIs that can be utilized to implement different strategies and methods in these fields.
Keywords: Sign Language Recognition, Live Camera, SVM, Gesturing, Lloyd’s Algorithm, Audio Output, Tensorflow, CNN.
Scope of the Article: Algorithm Engineering