B2B: Computer Vision

Table of Contents

1. About the Project
2. Project Goals
3. Roadmap
4. Project Structure
5. Contributing
6. License
7. Contact

About The Project

This repository contains a collection of resources and notes for reviewing fundamental concepts in computer vision. The goal is to provide a structured and comprehensive refresher on core topics, suitable for both beginners looking to solidify their understanding and experienced practitioners seeking to reinforce their knowledge base.

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Project Goals

• Consolidate Foundational Knowledge: To create a readily accessible and well-organized resource for key computer vision concepts.
• Curate High-Quality Resources: To gather and link to valuable learning materials, such as tutorials, papers, and online courses.
• Facilitate Self-Learning: To provide a framework for independent study and review.
• Promote Understanding: To clarify complex topics and provide intuitive explanations.

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Roadmap

This project is under active development. The following topics are planned to be covered (check the individual folders and files for current progress):

• Image Formation and Representation: Digital image basics, color spaces, image filtering.
• Feature Detection and Extraction: Edge detection, corner detection, SIFT, SURF, ORB, feature descriptors.
• Image Segmentation: Thresholding, region growing, graph-based segmentation, convolutional neural networks for segmentation.
• Object Recognition and Detection: Traditional methods (e.g., HOG, Haar cascades), deep learning methods (e.g., CNNs, R-CNNs, YOLO, SSD).
• Motion Estimation and Tracking: Optical flow, Lucas-Kanade algorithm, Kalman filtering, particle filtering.
• Image Registration: Transformations, feature matching, iterative closest point (ICP).

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Project Structure

Directory Structure

Usage Instruction

• For those who use Pipy

• For those who want to use uv

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Contributing

Contributions are welcome! If you find any errors, want to add new topics, or improve existing materials, please feel free to open an issue or submit a pull request. All contributions should follow the established style and format guidelines.

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License

[Specify your license here, e.g., MIT License]

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Contact

• Contact me via: LinkedIn | facebook

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This project is a work in progress. More content will be added over time. Check back regularly for updates!