avb6403 / CourtVision

Tennis ball detection and recognition system

Real-Time Image Processing and Analysis System

Project Overview

This project is designed to perform real-time image processing and pose analysis using a Zynq processor, integrating with MATLAB for processing and Unity for visualization.

System Architecture

Components:

• Image Processing Core: A dedicated module for initial image processing. It performs real-time operations such as filtering, edge detection, or noise reduction.
• VDMA (Video Direct Memory Access): Multiple VDMA blocks are used for efficient data transfer between the image processing core, Zynq processor, and the memory components without CPU intervention.
• Zynq Processor: The central processing unit that manages the flow of data, processes images, and communicates with external tools like MATLAB and Unity.
• MATLAB: Used for advanced image processing and analysis, including pose estimation algorithms.
• Unity: A game engine used for the visualization of processed data, showing the pose estimation in a 3D environment.

Data Flow:

1. Raw Images: The initial images are captured and fed into the system.
2. Image Processing Core: Raw images are processed using the core.
3. VDMA: The processed images are then passed through VDMA to the Zynq processor.
4. Zynq Processor: Further image processing and analysis take place here.
5. MATLAB: The Zynq Processor sends images to MATLAB for pose estimation.
6. Unity: The estimated pose is visualized in the Unity environment.

Interface:

• The system utilizes 64-bit interfaces for data transfer between the various components to ensure high throughput and efficient processing.
• Control Lines are used between the Zynq Processor and MATLAB to manage the flow of data and synchronization of processes.

Usage Scenarios

This system can be employed in various applications such as:

• Real-time surveillance for security purposes.
• Motion capture for animation and gaming.
• Sports analytics to analyze athletes' performance.

Enhancements

• Implementing custom algorithms on the Image Processing Core for specialized image processing tasks.
• Optimizing VDMA settings to handle higher resolution images without compromising real-time performance.
• Expanding the interface with Unity to include more complex visualizations and interactive elements.

---

For more detailed documentation, please refer to the individual component guides and the system integration manual.