Gesture Recognition Case Study

This case study aims at the automatic interpretation of gestures in order to offer new possibilities to interact with machine and to design more natural and more intuitive interactions with computing machines.

Table of Contents

• Problem Statement
• Objectives
• Structure of Case study
• Technologies-used
• Acknowledgements

Problem Statement:

• The company called Home Electronics which manufactures state of art televisions and the company wants to develop a cool feature in the smart-TV that can recognise five gestures performed by the user which will help users control the TV without using the remote.

• The gestures are continuously monitered by the webcam mounted on the TV. Each gesture corresponds to a specific command:

  1. Thumbs up : Increase the volume
  2. Thumbs down : Decrease the volumn
  3. Left swipe : Jump backwards 10 seconds
  4. Right swipe : Jump forward 10 seconds
  5. Stop : Pause the movie

Objectives:

• We are required to build a gesture recognition model using neural network which should have generators that are able to take batches of data without error and with optimized number of parameters so that the inference or prediction time should be less.
• The architecture we are going to use is:
  1. 3D Convs
  2. CNN + RNN stacked

Structure of Case study:

• Introduction
• Problem Statement
• Objectives
• Data Preprocessing (Creating the generator)
• Model Building
• Model Evaluation
• conclusion

Technologies Used

• Python version 3.9.13
• numpy library version 1.20.1
• pandas library version 1.2.4
• matplotlib library version 3.3.4
• seaborn library version 0.11.1
• tensorflow library version 2.9.0
• keras library version 2.9.0
• skimage library version 0.19.2
• git version 2.33.0.windows.1

References

1. https://github.com/amanrocks11/hand-gesture-recognition-deep-learning/blob/master/Gesture_Recognition_Final.ipynb
2. https://github.com/prateekralhan/Gesture-Recognition-Case-study-IIITB-Assignment-/blob/master/Gesture_Recognition_Case-Study_final.ipynb
3. https://smitan94.github.io/Gesture-Recognition-Neural-Network/

Contact

Created by [https://github.com/atharvapathak] - feel free to contact me!

1. Atharva - atharvapathakb2w@gmail.com