Emotion Detection Computer Vision Project

Krishna Gupta

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Classes (5)
Angry
Fearful
Happy
Neutral
Sad
Description

Emotion Detection Model for Facial Expressions

Project Description:

In this project, we developed an Emotion Detection Model using a curated dataset of 715 facial images, aiming to accurately recognize and categorize expressions into five distinct emotion classes. The emotion classes include Happy, Sad, Fearful, Angry, and Neutral.

Objectives:

  • Train a robust machine learning model capable of accurately detecting and classifying facial expressions in real-time.
  • Implement emotion detection to enhance user experience in applications such as human-computer interaction, virtual assistants, and emotion-aware systems.

Methodology:

  1. Data Collection and Preprocessing:

    • Assembled a diverse dataset of 715 images featuring individuals expressing different emotions.
    • Employed Roboflow for efficient data preprocessing, handling image augmentation and normalization.
  2. Model Architecture:

    • Utilized a convolutional neural network (CNN) architecture to capture spatial hierarchies in facial features.
    • Implemented a multi-class classification approach to categorize images into the predefined emotion classes.
  3. Training and Validation:

    • Split the dataset into training and validation sets for model training and evaluation.
    • Fine-tuned the model parameters to optimize accuracy and generalization.
  4. Model Evaluation:

    • Evaluated the model's performance on an independent test set to assess its ability to generalize to unseen data.
    • Analyzed confusion matrices and classification reports to understand the model's strengths and areas for improvement.
  5. Deployment and Integration:

    • Deployed the trained emotion detection model for real-time inference.
    • Integrated the model into applications, allowing users to interact with systems based on detected emotions.

Results: The developed Emotion Detection Model demonstrates high accuracy in recognizing and classifying facial expressions across the defined emotion classes. This project lays the foundation for integrating emotion-aware systems into various applications, fostering more intuitive and responsive interactions.

Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            emotion-detection-y0svj-nou9r_dataset,
                            title = { Emotion Detection Dataset },
                            type = { Open Source Dataset },
                            author = { Krishna Gupta },
                            howpublished = { \url{ https://universe.roboflow.com/krishna-gupta-8u7ie/emotion-detection-y0svj-nou9r } },
                            url = { https://universe.roboflow.com/krishna-gupta-8u7ie/emotion-detection-y0svj-nou9r },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { dec },
                            note = { visited on 2025-03-07 },
                            }
                        
                    

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