Five Point Feature Recognition of Face and Body for Driver Safety in Real Time Mobile Applications
Eben Sophia P1, Naveen Kumar S2, Selvamani M3, Surya S4, Venkat Balaji B S5
1Eben Sophia P, Assistant Professor, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore (TamilNadu), India.
2Naveen Kumar S, Student, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore (TamilNadu), India.
3Selvamani M, Student, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore (TamilNadu), India.
4Surya S, Student, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore (TamilNadu), India.
5Venkat Balaji B S, Student, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore (TamilNadu), India.
Manuscript received on 10 June 2019 | Revised Manuscript received on 17 June 2019 | Manuscript Published on 19 June 2019 | PP: 574-579 | Volume-8 Issue-8S June 2019 | Retrieval Number: H10970688S19/19©BEIESP
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© 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: In this project step by step implementation of facial recognition and body language recognition using open source algorithm has been explained. The use of body language as a natural interface serves as a motivating force for research in gesture taxonomies, its representations and recognition techniques, software platforms and frameworks which is discussed briefly in this paper. It focuses on the three main phases of body language and face expression i.e. detection, tracking and recognition. Different application which employs body language for efficient interaction has been discussed under core and advanced application domains. This paper also provides an analysis of existing literature related to gesture recognition systems for human computer interaction by categorizing it under different key parameters. Using this application the safety of drivers will be assured.
Keywords: Facial Recognition, Android Application, Driver Safety.
Scope of the Article: Economics of Energy Harvesting Communications