Facial Emotion RecognitionUsing Active Shape Models

Anukriti Dureha7CSE2A2305210153

Project Objective

Identify 5 classes of emotions of a given facial image by reconstructing facial models using Active Shape Modeling (ASM)

Neutral

Joy

Sadness

Surprise

Anger

5 Classes of Emotions

Six universal emotions

proposed by Ekman & Freisen

Project Methodology

Labeling

Landmark Features

Eye Brows

Nose

LipsChin

Eyes

Reference Model for Labeling

Landmark points Eg. of a Hand-Labeled Image

Shape Modeling

Shape Alignment

Principle Component Analysis

Model-Fitting

Emotion Classification

Start

Input: Model representation Read Mean

Models

Calculate Euclidean Distance between Mean

& Model- Rep

Stop

Output: Emotion

Parameters for Shape Modeling

Set of Images Used

Training Set

Testing Set

Results-Alignment of Shapes

Original Set of Images

Aligned Set of

Images

Results-Mean Models

Neutral Joy Surprise

Sad Anger

Results-Emotion Recognition

Confusion Matrix

Future Implications

Incorporating Texture Models

Use of Better Classification Techniques.

THANK YOU!