This is the presentation regrding the project of emotion recognition using deep learning approach

1. Emotion Recognition
Under the Guidance of:
Mrs. Sumedha Dasgupta
& Mr. Samiran Basak
Submitted By:
Satyaki sarkar(19)
Shashawta Chanda(17)
Sayak Bhattacharya(18)
Saheli Nandi(22)
Dishari Debnath (35)

2. CONTENTS
•Requirement of Emotion Recognition
•Objectives
•Challenges
•Enhancement that can be done
•Method
•Feature points
•Facial Expression
•Steps in Process
•Classifier Performance
•Packages used
• Working
•Modules
•References

3. Requirement of Emotion Recognition

4. Objectives
To predict a person’s emotion based on his face images, video frames
like:
• Analyzing the image and predict the expression of the person.
• To predict the current emotional state of prisoners and criminals.
• To predict expression of children who are affected by autism.

5. Challenges
• Low-intensity & less expressions.
• Data collection is expensive and time-consuming.
• Recognizing precise expression from a variety of
expression forms of different people.

6. Enhancement that can be done
User’s emotion using its facial expressions will be detected. These
expressions can be derived from the live feed via system's camera
or using web cameras.

7. Methods
We can use face detection approach for Emotion recognition purposes.

8. Feature points

9. Facial Expression
Prototypical facial expressions are anger, disgust, fear,
happiness, sadness, neutral and surprise. Contempt was
subsequently added as one of the basic emotions.
.

10. Steps in Process

11. Classifier Performance

12. Packages Used
We can use Java,C,Matlab,Python etc.But we use Python
because Hardware requirement is low and has many inbuilt
library functions.
Functions like:
Numpy,Scipy,Mathplotlib,Opencv etc.

13. Working
DATASET TRAINING:

14. Modules
• Module 1:- Data analysis
• Module 2:- Training the dataset
• Module 3:-Data identification
Related Works
• Face detection
• Missing Person identification
• Object detection
• Vehicle detection
• Pedestrian identification

15. References
•[1] L. Franco, Alessandro Treves ―A Neural Network Facial Expression Recognition
System using Unsupervised‖ Local Processing, Cognitive Neuroscience Sector – SISSA.
•[2] C. L. Lisetti, D. E. Rumelhart ―Facial Expression Recognition Using a Neural
Network‖ In Proceedings of the 11 th International FLAIRS Conference, pp. 328—332,
2004.
•[3] C. Busso, Z. Deng , S. Yildirim , M. Bulut , C.M. Lee, A. Kazemzadeh , S.B. Lee, U.
Neumann , S. Narayanan Analysis of Emotion Recognition using Facial Expression ,
Speech and Multimodal Information, ICMI‘04, PY, USA, 2004
•[4] Claude C. Chibelushi, Fabrice Bourel ―Facial Expression Recognition: A Brief
Tutorial Overview‖.
•[5] C. D. Katsis, N. Katertsidis, G. Ganiatsas, and D. I. Fotiadis, Toward Emotion
Recognition in CarRacing Drivers:A Biosignal Processing Approach, IEEE Transactions
On Systems, Man, And Cybernetics—Part A: Systems And Humans, Vol. 38, No. 3,
2008. [6] ANDREASSI, J. L. (2000): ―Psychophysiology: human behavior and
physiological response‖ (Lawrence Erlbaum Associates, New Jersey, 2000)

16. THANK YOU