language: en
tags:
- computer-vision
- image-classification
- hand-gesture-recognition
- cnn
- deep-learning
license: mit
Hand Gesture Recognition Dataset for Classroom Control
📝 Description
This dataset is designed for training and evaluating computer vision models for hand gesture recognition. It contains images of different hand gestures that can be used for smart classroom systems, human-computer interaction, and real-time gesture-based control applications.
The dataset is suitable for beginners and intermediate researchers working on convolutional neural networks (CNNs), deep learning, and image classification tasks.
🎯 Purpose
The main goal of this dataset is to enable the development of an AI system that can recognize hand gestures and perform actions such as:
- Controlling presentation slides
- Detecting student participation (raise hand)
- Touchless system interaction
- Gesture-based commands
🧩 Classes
The dataset contains 5 hand gesture classes:
- ✋ Stop
- 👍 Thumbs Up
- 👎 No
- 👆 Raise Hand
- ✌️ OK
📊 Dataset Details
- Total Images: 500
- Number of Classes: 5
- Images per Class: 100
- Image Type: RGB images
We developed this dataset as part of a hand gesture recognition project focused on smart classroom applications and real-time human-computer interaction.
- Zaheer Abbas — zaheeramini4040@gmail.com
- Muniza Ali — alymuniza@gmail.com
- Wajida Bano — wajidabano75@gmail.com