Detection of Facial Micro Expressions and Textual-Tracking for Paralyzed Using Computer Vision

Authors

  • Mathad SG Dept. of Information Science and Engineering, Global Academy Of Technology, Bangalore, India
  • Pruthvi LR Dept. of Information Science and Engineering, Global Academy Of Technology, Bangalore, India
  • Sanjana CS Dept. of Information Science and Engineering, Global Academy Of Technology, Bangalore, India
  • B Akash Dept. of Information Science and Engineering, Global Academy Of Technology, Bangalore, India
  • Deepthi VS Visvesvaraya Technological University, Belagavi, India

DOI:

https://doi.org/10.26438/ijcse/v7i12.6266

Keywords:

Formatting real time interactive eye blink system, Locked-In Syndrome, Amyotrophic Lateral Sclerosis (ALS), Tetraplegia, sentiment-based music system and video streams

Abstract

Paralysis is the loss of voluntary muscle control. Many people cannot move a single part of their body. Even though the paralyzed people are cognitively aware of their surroundings, they have no means of communication. The paralyzed people have lost their ability to talk, type, etc. These victims affected by Locked-In Syndrome have their thoughts and ideas trapped inside of them. Usually people with paralysis have total control over their eye movement. Therefore this project aims to build a real time interactive eye blink system that allows paralyzed people to easily express themselves. Some people who are affected with Amyotrophic Lateral Sclerosis (ALS) and Tetraplegia can also express their emotions (Eg: smile) and hence these expressions can be used as commands for performing some helpful tasks. We aim to show this by implementing sentiment-based music system to play music by retrieving their current mood via video streams.

References

[1] Christopher and Dana Reeve Foundation: christopherreeve-stats about paralysis.

[2] MedicineNet :stats for locked in syndrome

[3] SpinalCord.com: spinal cord injury statistics

[4] IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions 2017 on “An Intelligent Music Player based on Emotion Recognition”.

[5] 2012 Fourth International Conference on “Digital Home”.

[6] 2nd IEEE International Conference on Computational Systems and Information Technology for Sustainable Solutions 2017 on “An Intelligent Music Player based on Emotion Recognition”.

[7] IEEE International Conference on Computer Vision and Information Security (CVIS) “A Novel Method for Eye Tracking and Blink Detection in video frames”.

[8] Research gate Conference Paper for “Automatic Eye Blink Detection Using Consumer Web Cameras”.

[9] CS 231M Project Paper Spring Quarter at Stanford University for “Real Time Blink Detection For Burst Capture”.

[10] 21st Computer Vision Winter Workshop, Luka Cehovin, RokMandeljc, VitomirStruc on “Real-Time Eye Blink Detection using Facial Landmarks”.

[11] 9th International Conference on Computational Intelligence and Communication Networks on “Human computer interaction by eye blinking on real time”.

[12] International Conference on Electronics, Communication and Aerospace Technology ICECA 2017 on “face detection and tracking”.

[13] Institute of Biomedical Engineering, National Central University on “Implementation of an Eye-blink-based Communication Aid for People with Severe Disabilities”.

[14] Institute of Biomedical Engineering, National Central University on “Implementation of an Eye-blink-based Communication Aid for People with Severe Disabilities”.

[15] International Conference on “Identifying Accuracy of Social Tags by Using Clustering Representations of Song Lyrics”.

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Published

2019-12-31
CITATION
DOI: 10.26438/ijcse/v7i12.6266
Published: 2019-12-31

How to Cite

[1]
S. G. Mathad, L. Pruthvi, C. Sanjana, A. B, and V. Deepthi, “Detection of Facial Micro Expressions and Textual-Tracking for Paralyzed Using Computer Vision”, Int. J. Comp. Sci. Eng., vol. 7, no. 12, pp. 62–66, Dec. 2019.

Issue

Vol. 7 No. 12 (2019): IJCSE December Edition

Section

Research Article

License

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