Patrik Huber
Principal Computer Vision Engineer at University of Leeds
York, England, United Kingdom
Summary
🤩
Rockstar🎓
Top SchoolPatrik Huber is a Principal Computer Vision Engineer and founder with 14 years of experience building real-time 3D face tracking and reconstruction systems for healthcare and creative industries. He leads applied research and product development at Mimetrik while commercializing a state-of-the-art statistical 3D face model through 4dface Ltd. Formerly a Lecturer at the University of York and a visiting researcher at Surrey and Leeds, he blends academic rigour with production engineering to solve clinically relevant vision problems in dentistry. A seasoned modern C++ programmer, he contributes to major open-source projects like OpenCV and GLM, improving build compatibility and numerical robustness. His work spans face landmarking, contour/edge fitting and model-based pose normalisation, enabling real-time analysis on video. Patrik’s uncommon combination of deep research on 3D morphable models and hands-on release engineering makes him effective at taking vision algorithms from papers to production.
13 years of coding experience
9 years of employment as a software developer
Master’s Degree, Computer Science, Master’s Degree, Computer Science at Universität BaselDoctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at University of Surrey
English, German, French
Github Skills (29)
cpp-library10
opencv10
c-language10
lib10
mathematics10
data-serialization10
code-library10
cmake10
math10
serialization10
build-automation10
computer-vision10
type-conversion10
cpp10
cprogramming-language10
Programming languages (15)
Github contributions (5)
patrikhuber/4dface
Jan 2016 - Dec 2018
Real-time 3D face tracking and reconstruction from 2D video
Role in this project:
ML Engineer
ML EngineerContributions:5 releases, 34 commits, 4 PRs in 2 years 11 months
Contributions summary:Patrik primarily contributed to the development of a real-time 3D face tracking and reconstruction application. Their work involved integrating and updating the core libraries and algorithms for face detection, landmark detection, and 3D model fitting. The user incorporated contour and edge fitting techniques to enhance the accuracy of the 3D model reconstruction. Furthermore, the user updated the project to incorporate newer versions of core libraries.
2d-videoreconstructioncomputer-visiontrackingface-tracking
opencv/opencv
May 2015 - Feb 2018
Open Source Computer Vision Library
Role in this project:Automation Engineer / Build & Release Engineer
Automation Engineer / Build & Release EngineerContributions:7 commits, 5 PRs, 37 comments in 2 years 10 months
Contributions summary:Patrik's contributions primarily revolve around enhancing the build and compatibility of the OpenCV library. They focused on adding and refining support for different Visual Studio versions, specifically VS2015 and VS2017, by modifying CMake scripts. This included ensuring proper version detection and correct installation paths for the generated binaries. Furthermore, the user's work facilitated compatibility improvements in the build process for different compiler versions, contributing to the overall maintainability of the project.
pythonvisiondeep-learningc-plus-pluscomputer-vision
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