Maxim Mikhnevich


Québec (QC), Canada | contact@maximmikhnevich.com


Summary

Experienced Computer Vision researcher specializing in the development of advanced computer vision systems. Skilled in 2D and 3D camera calibration, projector calibration, image processing, and 3D reconstruction. Proficient in C++, Matlab, Python, OpenCV, C#.

Professional Experience

2024 - present
Computer Vision Project Manager Centre de robotique et de vision industrielles Inc. (CRVI)
2015 - 2023
Computer Vision Researcher National Optics Institute (INO)
2011 Sep. – 2011 Dec.
Teaching Assistant Université Laval Vision Numérique (GIF-4100)

Education

2008-2015
PhD, Computer Science Université Laval
Thesis title: Unsupervised Reconstruction of the Visual Hull
  • Developed a 3D reconstruction algorithm for objects with complex reflective properties, such as glass or aluminum.
  • Created an image segmentation and boundary refinement algorithm based on Graph Cuts.
  • Conducted real and virtual data acquisition using a light field setup and 3ds Max.
  • Authored one journal paper and presented two conference papers at international conferences.
2006-2008
Master’s Degree in Information Technology Lappeenranta University of Technology
Thesis title: Multi-sensor Simultaneous Localization and Mapping.
  • Developed a SLAM algorithm for navigation in a 3D environment using Kalman filter and SIFT features.
  • Conducted data acquisition with a Pioneer P3-DX robot and Bumblebee2.
2001-2006
Bachelor’s Degree in Applied Mathematics, Rostov State University

Publications

2017
Camera calibration method using a calibration target, 9965870
2016
Passive calibration board for alignment of VIS-NIR, SWIR and LWIR images, L. St-Laurent, M. Mikhnevich, A. Bubel, D Prévost, Quantitative InfraRed Thermography(QIRT)
2014
Shape from silhouette in space, time and light domains, M. Mikhnevich, D. Laurendeau, International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP)
2012
Unsupervised visual hull extraction in space, time and light domains, Computer Vision and Image Understanding (CVIU), M. Mikhnevich, P. Hébert, D. Laurendeau
2011
Shape from silhouette under varying lighting and multi-viewpoints, The Conference on Computer and Robot Vision (CRV), M. Mikhnevich, P. Hébert