Real Time Facial Expression Recognition using Eigen Faces - By Aadesh - - PowerPoint PPT Presentation

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real time facial expression recognition using eigen faces
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Real Time Facial Expression Recognition using Eigen Faces - By Aadesh - - PowerPoint PPT Presentation

Nov 22, 2023 26 likes •210 views

Summer Intern Project on Real Time Facial Expression Recognition using Eigen Faces - By Aadesh M Bagmar (U12 CO 092) Project Guide: Dr. M.A.Zaveri Computer Engineering Department Brief The project aims at developing a robust system for real

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Summer Intern Project on Real Time Facial Expression Recognition using Eigen Faces

  • By Aadesh M Bagmar (U12 CO 092)

Project Guide: Dr. M.A.Zaveri

Computer Engineering Department

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The project aims at developing a robust system for real time analysis and detection of facial expressions and clearly classify them into their respective emotion states using Eigen Face models.

Brief

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  • Platform :

Linux

  • Library :

OpenCV

  • Coding Language :

C++ and Python

  • A color camera.
  • OpenCV API’s.
  • Databases:
  • Yale Faces
  • Jaffe Database

Resources Used

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Working

The project involves the following steps: Creating the Database using the trainer app. Pre-Processing the image. Training the database. Predicting the outcome/result using the tester app.

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The DATABASE

SAD HAPPY SURPRISE DISGUST The Database showing the 4 expressions given to the trainer app.

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Results

Eigen Faces created by the Recognizer Mean Face

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SIMULATION

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Boundary Conditions for the system

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Future Prospects

  • Integration with Speech and Video Processing for better analysis.
  • Development of an Android application for driver analysis system.
  • Making the application less susceptible to boundary values and making it more robust.
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References

Books: Digital Image Processing by Rafael Gonzales and M Woods. Online Lecture series: Image and Video Processing by Guillermo Spiro, Duke University. (coursera.com) Research Papers: 1.

  • M. Turk and A. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3 (1), 1991a. URL http://www.cs.ucsb.edu/ mturk/Papers/jcn.pdf.

2.

  • M. A. Turk and A. P. Pentland. Face recognition using eigenfaces. In Proc. of Computer Vision and Pattern Recognition, pages 586-591. IEEE, June 1991b.

3. Viola and Jones, Face Detection using Haar wavelets. IEEE, 2001. 4.

  • P. Viola and M. J. Jones, Robust real-time face detection, International Journal of Computer Vision, 57 (2004), pp. 137–154. http://dx.doi.org/10.1023/B:VISI.0000013087.49260.fb.

Websites: 1. www.opencv.org 2. www.ieeeexplore.ieee.org 3. www.ipol.im 4. http://openbio.sourceforge.net/resources/eigenfaces/eigenfaces-html/facesOptions.html 5. www.cognotics.com

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Acknowledgements

I would like to take this opportunity to express my profound gratitude to

  • Dr. M.A.Zaveri for his exemplary guidance and monitoring during the

entire course of this project. I feel deeply honored to express my deep thanks to dean R&C for giving me this Golden Opportunity through the departmental summer fellowship program.

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