Alexander Panov
Nizhniy Novgorod, Nizhniy Novgorod, Russia
Summary
🤩
Rockstar🎓
Top SchoolAlexander Panov is a C/C++ developer and computer vision engineer with nine years’ experience improving algorithms and production-grade CV systems, currently at Xperience.ai and teaching practice at Nizhniy Novgorod State University. He has a strong track record in OpenCV contributions—over 100 PRs—where he revamped the ArUco module, boosted QR detection/decoding rates, and hardened Charuco marker interpolation and tests. His work spans algorithm design, performance profiling with Intel VTune, CI reliability, and Android/OpenCL samples, demonstrating both research-led development and production performance tuning. Alexander also built a Python benchmarking pipeline for synthetic augmentation and validated detectors on a 1000+ real QR code dataset, yielding substantive accuracy gains. Beyond software, he prototypes hardware projects with microcontrollers, 3D printing and drones, which informs his practical systems thinking and embedded-aware CV solutions.
10 years of coding experience
4 years of employment as a software developer
Магистр, Прикладная математика и информатика, Магистр, Прикладная математика и информатика at State University of Nizhni Novgorod named after N.I. Lobachevsky (UNN)
Russian, English
Github Skills (9)
computer-vision10
opencv10
c-language10
cprogramming-language10
image-processing10
test-automation10
testing10
unit-testing9
python8
Programming languages (3)
Github contributions (5)
opencv/opencv_contrib
Nov 2021 - Dec 2022
Repository for OpenCV's extra modules
Role in this project:
Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:142 reviews, 58 commits, 41 PRs in 1 year 1 month
Contributions summary:Alexander's commits primarily focus on enhancing the ArUco and ChArUco marker detection modules within the OpenCV contrib repository. They implemented fixes for issues related to marker shape and introduced new tests. Furthermore, they added functionality to improve the interpolation of Charuco corners and incorporated testing for various aspects of the Charuco board, including subpixel accuracy, diamond marker detection, and thread safety. The contributions demonstrate a focus on improving the robustness and reliability of the marker detection and pose estimation functionalities.
opencv/opencv
Aug 2021 - Dec 2022
Open Source Computer Vision Library
Role in this project:Back-end Developer & Test Automation Engineer
Back-end Developer & Test Automation EngineerContributions:403 reviews, 23 commits, 54 PRs in 1 year 5 months
Contributions summary:Alexander contributed to the OpenCV library by implementing and adding new tests. Their work includes adding tests for the `minAreaRect`, `findMinEnclosingTriangle`, and QR code detection. The user also fixed bugs and added notes regarding the Python version and documentation. Additionally, they refactored parts of the code and addressed warnings related to Quirc.
computer-visionc-plus-plusdeep-learningimage-processing
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