neozhaoliang/surround-view-system-introduction

📹 Surround‑View System Introduction

What it is – A small, self‑contained open‑source implementation of a vehicle‑mounted surround‑view (bird‑eye) camera system. It walks through the full pipeline:

• Calibration of multiple fisheye cameras
• Projection from each camera’s view to a common ground plane
• Stitching of the four (or more) projected images into a seamless 360° top‑down view
• Real‑time execution so the composite can be displayed live.

Why it matters – Surround‑view systems are a core perception component for modern driver‑assist and autonomous‑driving stacks. Public codebases are rare, so this repo gives newcomers a concrete reference they can compile, run, and extend.

Key contents

• src/ – C++/Python (as in the repo) implementation of calibration, projection matrices, and stitching logic.
• doc/ – Detailed step‑by‑step guide (Chinese + English) covering hardware setup, calibration procedures, and how to launch the real‑time demo.
• data/ – Sample calibration files and test video streams.

Typical workflow

1. Capture calibration patterns with each camera.
2. Run the calibration script to compute intrinsic/extrinsic parameters.
3. Configure the projection matrices for the desired ground‑plane distance.
4. Start the real‑time stitching program; the four camera feeds are merged into a single top‑down image displayed on screen.

Who should look at it – Students, hobbyists, or early‑stage robotics teams wanting a hands‑on example of multi‑camera vision without diving into a full‑blown automotive SDK.

How to contribute – The author encourages issues and pull requests to improve documentation, add support for more cameras, or integrate GPU‑accelerated stitching.

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Quick start (as described in the README)

# Clone the repo
git clone https://github.com/neozhaoliang/surround-view-system-introduction.git
cd surround-view-system-introduction

# Follow the English guide in doc/en.md for calibration and running