ROS Stereo Vision

A ROS-based stereo vision system designed for tennis ball tracking and analysis

Project Overview

This ROS-based stereo vision system was developed for tennis ball tracking and analysis, demonstrating advanced computer vision techniques in robotics applications. The system utilizes stereo cameras to provide depth perception and real-time object detection capabilities.

The project implements sophisticated computer vision algorithms including object detection, tracking, and 3D position estimation. It's designed to work within the Robot Operating System (ROS) framework, making it easily integrable with other robotic systems and applications.

The system can track tennis balls in real-time, providing position data, velocity estimation, and trajectory prediction. This makes it suitable for sports analysis, robotic tennis applications, or any scenario requiring precise object tracking in 3D space.

Key Features:

  • Real-time stereo vision processing
  • Tennis ball detection and tracking
  • 3D position estimation
  • Trajectory prediction
  • ROS integration
  • OpenCV-based computer vision
Language Python
Category Computer Vision
Application Sports Analysis
License MIT
Technologies
Python ROS Computer Vision OpenCV Stereo Vision

Applications & Use Cases

Sports Analysis

Tennis ball tracking for performance analysis, coaching, and automated sports statistics collection.

Robotic Applications

Integration with robotic systems for automated ball collection, training robots, or interactive games.

Computer Vision Research

Platform for testing and developing new computer vision algorithms for object tracking and 3D reconstruction.

Education

Educational tool for teaching computer vision, robotics, and stereo vision concepts.

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